DEPARTMENT OF AGRICULTURAL ... - University of Nigeria
Transcript of DEPARTMENT OF AGRICULTURAL ... - University of Nigeria
UNIVERSITY OF NIGERIA, NSUKKA DEPARTMENT OF AGRICULTURAL ECONOMICS
GENDER AND RESOURCE USE EFFICIENCY IN COCOYAM
PRODUCTION IN ANAMBRA STATE, NIGERIA.
AN M.Sc DISSERTATION SUBMITTED TO
THE DEPARTMENT OF AGRICULTURAL ECONOMICS
UNIVERSITY OF NIGERIA, NSUKKA
BY
OKOYE, FRANCISCA .UZOOYIBO.
PG/M.Sc/08/49854
SUPERVISOR: PROF. C. U. OKOYE
HEAD OF DEPARTMENT: PROF.E.C.OKORJI
FEBRUARY, 2014
TITLE PAGE
GENDER AND RESOURCE USE EFFICIENCY IN COCOYAM PRODUCTION IN
ANAMBRA STATE
BY
OKOYE, FRANCISCA.UZOOYIBO
REG NO: PG/M.Sc/08/49854
AN M.Sc DISSERTATION SUBMITTED TO THE DEPARTMENT OF
AGRICULTURAL ECONOMICS, FACULTY OF AGRICULTURE, UNIVERSITY OF
NIGERIA, NSUKKA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR
THE AWARD OF MASTERS DEGREE IN AGRICULTURAL ECONOMICS WITH
SPECIALIZATION IN RESOURCE AND ENVIRONMENTAL ECONOMICS
FEBRUARY, 2014.
APPROVAL PAGE
GENDER AND RESOURCE USE EFFICIENCY IN COCOYAM PRODUCTION
IN ANAMBRA STATE, NIGERIA
BY
OKOYE, FRANCISCA UZOOYIBO
REG NO:PG/M.Sc/08/49854
A DISSERTATION SUBMITTED TO THE DEPARTMENT OF AGRICULTURAL
ECONOMICS IN FULFILMENT OF THE REQUIRMENTS FOR THE AWARD OF
MASTERS (M.Sc) DEGREE IN AGRICULTURAL ECONOMICS.
APPROVED BY:
…………………….. ……………………
Prof.C.U, Okoye Date
(supervisor)
………………………… ....…………………
Prof.E.C, Okorji Date
(Head, Dept. of Agric. Economics).
CERTIFICATION
Okoye Francisca.U. a post graduate student of the Department of Agricultural Economics,
University of Nigeria, Nsukka with Registration Number PG/M.sc/08/49854 has satisfactorily
completed the requirement of a research work for the award of masters Degree in Agricultural
Economics. The work embodied in this project is original and has not been submitted in part or
whole for the award of any Degree in this/any university.
____________________ ___________________
Prof. C.U, Okoye Prof. E.C, Okorji
Project Supervisor Head of Department
Date______________ Date_______________
________________________
External Examiner
Date_________________
DEDICATION
This work is dedicated to Almighty God for his grace, guidance and protection.
ACKNOWLEDGEMENT
I indeed owe a lot of gratitude, thanks and praises to God Almighty who has out of his
special mercies and favour kept me to see these days. My profound and heartfelt gratitude goes to
my Supervisor Prof. C.U. Okoye who stood out as an indispensable contributor to this work,
morally and technically. I jealously cherish Professors S.A.N.D. Chidebelu; E.C. Okorji; E.C.
Nwagbo; C.J. Arene; N. J. Nweze and (Mrs.) A. I. Achike, Doctors F.U. Agbo, Ben Okpupara; N.
Chukwuone and other academic staff of the Department of Agricultural Economics, UNN who
have contributed to the success of this work in one way or the other. I sincerely appreciate you all.
On a very important note, I wish to register my genuine appreciation to my dear friends
Taofeeq Amusa, Inyada Ladi, Mgbebu Ezekiel, Chinelo, Emeka Okoye, Rev. Fr. Maurice
Abasilim, Dr. Emeka Okoye and Chukwuemeka Kadurumba who has been my source of joy and
happiness throughout the course of study. I appreciate your kind gesture.
To my sweet parents, Chief and Mrs. Okoye Lazarus, honestly you are wonderful and
bunch of gift to me. God Almighty will continue to keep you in good health. My siblings Okoye
Calistus, Okoye Elijah, Okoye Chijioke, Okoye Amala, Okoye Chisom, including Ekenechukwu
Okafor, Chinonso Okafor and Chigozie Okafor (Adazion) I sincerely thank you for your care,
love and good wishes. I appreciate your words of encouragement that cannot be neglected in
telling any success story about this work.
Okoye, Francisca. U.
February, 2014
TABLE OF CONTENTS
Title Page i
Approval Page ii
Certification iii
Dedication iv
Acknowledgement v
Table of Contents vi
List of Tables viii
Abstract ix
CHAPTER ONE – INTRODUCTION 1
1.1 Background Information 1
1.2 Problem Statement 3
1.3 Objectives of the Study 4
1.4 Hypotheses of the Study 4
1.5 Justification of the Study 5
CHAPTER TWO - LITERATURE REVIEW 6
2.1 Under Utilization of Cocoyam 6
2.2 Potentials of Cocoyam 7
2.2.1 Nutritive Values of Cocoyam. 7
2.2.2 Economic Values of Cocoyam 8
2.2.3 Agronomic Values of Cocoyam 9
2.3 Gender Issues in Agriculture 9
2.4 Gender and Farm Input Delivery System, Supply and Productivity 11
2.5 Cost and Returns 13
2.6 Resource Problems and Resource Allocation of Rural Economies 13
2.6.1 Resource Problems 13
2.6.2 Rural Resource Allocation 14
2.7 Evidence of Resource Productivity and Efficiency Studies 16
2.8 Theoretical Framework 17
2.9 Analytical Framework 21
CHAPTER THREE: METHODOLOGY 23
3.1 Study Area 23
3.2 Sampling procedure 23
3.3 Data Collection. 24
3.4 Data Analysis 25
3.5 Hypotheses Testing 28
CHAPTER FOUR: RESULTS AND DISCUSSION 29
4.1 Socio-Economic Characteristics of the Respondents 29
4.2 Comparison of Mean Output of male and female Cocoyam Farmers 33
4.3 Estimation of Technical and Allocation Efficiency in Cocoyam Production 33
4.4 Comparision of Technical and Return to Scale of the male and Female Farmers 40
4.5 Cost and Returns of Male and Female Cocoyam Farmers 41
4.6 Problems Encountered by Cocoyam Farmers Based on Gender 42
CHAPTER FIVE: SUMMARY, CONCLUSIONS & RECOMMENDATION 44
5.1 Summary 44
5.2 Conclusion 45
53 Recommendation 45
REFERENCE 47
Appendix I: Estimated output of major agric commodities (000 tons) 58
LIST OF TABLES
Table 3.1: Selection of Cocoyam Farmers in the Study Areas 24
Table 4.1: Distribution of Male and Female Cocoyam Farmers According to Socio-economic
Characteristics 31
Table 4.2: Two Sample t-test of Cocoyam Output by Gender 33
Table 4.3: Maximum Likelihood Estimates of the Cobb-Douglas Stochastic Production
function for male and female farmers in Anambra State. 35
Table 4.4: Results of Multiple Regression Analyssis of Female Cocoyam Farmers 38
Table 4.5: Results of Multple Regression Analysis of Female Cocoyam Farmers 38
Table 4.6: Estimation of Allocative Efficiency for Male Cocoyam Farmers 39
Table 4.7: Estimation of Allocative Efficiency for Female Cocoyam Farmers 40
Table 4.8: Elasticities of Production for Male and Female Cocoyam Farmers 41
Table 4.9: Costs and Returns of Male and Female Cocoyam Farmers 42
Table 4:10: Distribution of male and female respondents according to constraints in cocoyam
production 43
Abstract The study was designed to investigate the gender and resource use efficiency in cocoyam
production in Anambra State, Nigeria. Socio-economic characteristics of the farmers were
determined as well as the production problems affecting the farmers in the study Area. The study
presents the results of analysis of data collected on 160 male and female cocoyam farmers across
two Agricultural zones. A multi-stage randomized sampling technique was used to select the
zones, blocks, circles and contact farmers Descriptive statistical tools such as percentages,
frequencies and mean were used in analyzing farmer’s socio-economic characteristics and
production problems. The result showed that women constituted a greater percentage (68.75%) of
those involved in cocoyam production in the state, which comprises those within who the age
range of 41 to 50 years. The Maximum Likelihood Estimation (MLE) technique was used in
estimating the technical efficiency and determinants of efficiency of male and female farmers
with the Cobb-Douglas production function as the lead model. The result of estimation of
technical efficiency using the Cobb- Douglas stochastic function showed that the coefficients of
male and female farmers for the production variables used were all positive. Cocoyam setts,
labour and fertilizer use were significant while capital inputs were not significant for female
cocoyam farmers. The result indicates that socio-economic conditions influenced technical
efficiency of both categories of farmers. The coefficients of determinants of efficiency used were
all positive except farm size that was negative and significant for both male and female cocoyam
farmers while age, level of education, extension contact, knowledge index were all positive and
significant for male farmers while other variables were not significant. Test of allocative
efficiency revealed that none of defined farmer groups achieved absolute allocative efficiency.
Male farmers underutilized fertilizer and over utilized other inputs in production while female
farmers over utilized all the inputs. This result suggests that there exists the possibility of
increasing output under existing level of technology through the use of lower levels of all inputs
by male and female farmers except fertilizer for males. There is also scope to use higher levels of
fertilizer for the male farmers. The result shows the mean output/kg of 2,450.20kg and 2,519.09kg
with an average net profit of N62, 592.87 and N88, 378.12 and BCR of N1.85 and N2.16 for the
male and female farmers respectively. This implies that cocoyam production was profitable in the
study area. The results also showed the elasticities of productions of male to be 0.43246 and that
of female to be 1.1987, this shows a decreasing return to scale for male cocoyam farmers and
increasing return for female cocoyam farmers. Finally, the survey revealed that most of the
farmers (male and female) encountered problems of root rot diseases at 90% and 90.91%
respectively.
CHAPTER ONE
INTRODUCTION
1.1: Background information
In Nigeria of about 140 million people, men constitute about 50.4% and women
49.6%(N.P.C, 2006).Both gender are responsible for producing nation’s food and one of the
major problems confronting mankind in recent times is food crisis (Ndukwu et al 2010).Gender
has often been misunderstood as being about the promotion of women only, but it focuses on the
relationship between men and women, their roles, access to and control over resources, division
of labour and needs. Men and Women are affected differently in their operation in factors like
markets and socio- economic environments. Women are more constrained than their men
counterparts in terms of access to credits, agricultural inputs, and information technology and so
on. Some crop are men’s, like yam production, while others like sweet potatoes and cocoyam
production are regarded as women’s especially in the southeastern Nigeria (Ndukwu et al 2010).
Dimelu et al (2009) reported that women are involved in crop production generally and cocoyam
production in particular
Agriculture is the largest single sector in the Nigeria economy, providing food, income
and employment for sustainable livelihood of both the rural and urban population (CBN, 2003).
Agriculture is the largest non-oil export earner and the largest employer of labour accounting for
88% of the non-oil foreign exchange earnings and 70% of the active labour force of the
population. Food crops constitute the largest component of the crops sub-sector of the Nigeria’s
agriculture (CBN,2003). Root and tuber crops which are among the most important groups of the
staple foods in many tropical African countries(Osagie,1998) Constitutes the largest source of
calories for Nigeria population(Olaniyan et al 2001)
Cocoyam originated from Asia and about forty (40) species are mostly grown in West
Africa (Asumugha and Mbanasor, 2002).Cocoyam,both Xanthosoma species and Colocasia
species belong to the family (Aracea).The cocoyam specie colocasia esculata in sub-Sahara
Africa was introduced to this continent one thousand or more years ago from South East Asia
while cocoyam specie Xanthosoma Mafafa was introduced more recently from tropical America
(11TA, 1992; FAO, 2005a).
Nigeria is the largest producer of cocoyam in the world, accounting for about 37% of the
total world output (FAO, 2007b; NRCRI, 2009). From 0.73 million metric tones in 1990,
cocoyam production in Nigeria rose to 3.89million metric tones in 2000 (Ojiako et al; 2007;) and
further by 30.30% to 5.068 million metric tones in 2007 (FAO, 2007b). Further estimate in
Nigeria, showed a figure of 5,387 million metric tones out of 11.77 million metric tones of world
output of cocoyam per annum since 2008 (FAO STAT, 2010).
Cocoyam ranks third in importance after cassava and yam among the root and tubers crops
cultivated in Nigeria (see Appendix 1) (FAO, 2005a, National Breau of Statistics, 2006, Okoye et
al; 2008). Cocoyam both Xanthosoma sp and colocasia sp is an important staple food in the plant
family, cultivated in South Eastern and South Western part of Nigeria (Onyenweaku et al, 2005;
Ojiakor et al, 2007; Chukwu et al, 2009). It is a food security crop variously grown by resource
poor farmers especially women who often intercrop it with yam, maize, plantain, banana,
vegetable (Ikwelle et al, 2003).
Cocoyam is highly medicinal for diabetic patients because it has low starch content, is
easily digestible and contains protein more than the other root tubers. The leaves of colocosia
esculenta have been shown to be a rich source of folic acid, ribo flavin, vitamin A and C, calcium
and phosphate (Arene and Ene, 1987). The leaves are consumed because they are rich in protein
and vitamins while the root is rich in carbohydrates and minerals (Duru and Uma, 2002).
Cocoyam is a useful cover crop and the corms are ready to harvest in 8 – 12 months (Uguru,
1996). The corms and cormels are boiled, baked and tubers are sometimes ground to produce
paste for use in stews and soups. Also in Southeast Asia, cocoyam leaves are consumed as a
green or dry vegetables and the stem is either cooked or eaten on its own or together with other
dietary staples or pounded into flour (Serem et al; 2008).The dried peeled corms are grinded to
produce flour which is considered to be as palatable as cassava flour but more nutritious
(Igbokwe, 2004).
In the traditional farming system women "own" and plant cocoyam after the men have
planted their yam, hence it is regarded as a women's crop (Igbokwe, 2004). As a result of male
out migration into urban and semi urban areas, certain task that were traditionally done by men
(e.g. ridging) are now being done by the women folk. Thus the gender based differentiation of
farm tasks appears to be disappearing. Some scholars believe and argue that majority of the
small scale farmers who produce the bulk of Nigeria's agricultural output especially cocoyam
are women. It is still their contention that women also play key roles in storage preservation,
processing, utilization and local marketing of agricultural produce (Dixon, 1983; Ekumankama
and Ekumankama, 1996). Females constitute the greater percentage of the Nigerian population
in the rural areas (Musa, 1987)
Given the importance of cocoyam and the fact that its cultivation is receeding, it
becomes compelling to examine the production methods, practices and resource inputs for its
production methods, practices and resource inputs for its production in other to identify
opportunities for improvements in terms of cultivation and efficient use of available resources.
Government research effort under cocoyam expansion programme had led to
development of several technologies aimed at adding value to cocoyam production (NRCRI,
1999). Also, dissemination of the improved technologies as well as advocacy supports for
overall development of cocoyam are effective strategies for optimizing utilization of the
abundant potentials associated with cocoyam in Nigeria.
3.1 Problem Statement
The resource allocation to cocoyam is significantly low when compared to other crops
such as yam and cassava. Technical difficulties involved in managing cocoyam, especially the
post harvest losses usually not encountered in the rival crops have made cocoyam comparatively
less attractive especially the male farmers thereby affecting productivity (Ekwe et al; 1999).
Cocoyam production in South Eastern Nigeria is threatened by some factors such as the cocoyam
root, not blight complex, high cost of labour, which is almost entirely manual (Okoye et al; 2008).
Also the preference of other crops to seriously cocoyam in household production, and
consumption decision became fundamental reasons for its neglect and under utilization. Empirical
findings of earlier research like (Dimelu et al; 2008) on cocoyam have reported reasons such as
high cost of labour, disease outbreak etc. for decline in output of cocoyam, none of these studies
tried to explain output decline from point of view of gendered use of production resources nor
did they consider that the people (women) who are left to carry on its production might have
some gender-related constraints in resource utilization which could affect entry into cocoyam
farming as well as productivity.
Hence, there is need to sustain the level of production through productivity and
resource use studies, agricultural production in Nigeria has always been seen as dominated by
men and this assumption undermines the women involvement in agricultural production.
Okoye et al (2007) pointed out that women farmers for several years have been the pillars of
cocoyam production. Unfortunately as noted by Durno and Stuart (2005), they are not
recognized as farmers and are not critically involved in the process of farm problem analysis,
planning and decision making, or provided with the training, credit and support they need.
They equally noted that development opportunities are usually offered to those who are better
off and better educated, majority of whom are men. Many extension programmes are focused
on the "family headed" that is the husband as women are considered as helpers in the farm.
The presumption is that women are less economically efficient than men in Agricultural
production.
The problems of this study therefore are to analyze the possible ways in which
equitable gender involvement and resource use will help increase output in cocoyam
production in Anambra state.
In view of this forgoing, this study attempted to answer the following questions:
- to what extent are men and women involved/engaged is cocoyam production?
- do women have access to the same quantity and quality of resources as men in
Cocoyam production?
- does being a woman influence how resources are applied for cocoyam production?
- how efficiently do women farmers employ resources for cocoyam production?
- what are the sources of inefficiency in women's use of cocoyam resources?
1.3 Objective of the study
The broad objective of this study was to determine by gender the resource use efficiency in
cocoyam production in Anambra State.
The specific objectives are to:
(i) examine the socio-economic characteristics of cocoyam farmers in Anambra State
(ii) estimate and compare the mean output of men and women cocoyam farmers.
(iii) estimate and analyse the technical and allocative efficiencies of cocoyam farmers by
gender
(iv) compare the technical and returns to scale of the farmers based on gender.
(v) determine the profitability of cocoyam farming by gender.
(vi) identify the major problems/constraints faced by the men and women cocoyam
farmers.
(vii) Recommendation based on the research findings
1.4 Statement of Hypotheses
The following hypotheses were tested:
HO1 There is no significant difference in technical and allocative efficiency of the cocoyam
in the use of farm resources across gender
HO2 There is no significant difference in the mean output of male and female cocoyam farmers
HO3 Cocoyam production is not profitable in the study area
1.5 Justification of the Study
Improving cocoyam productivity, achieving self sufficiency in cocoyam production and
other food crops has been a major concern to scholars and policy makers as well as farmers
themselves, majority of who live in the rural areas (Okoye et al; 2007). This is more worrisome
considering the fact that Nigeria is endowed with rich and abundant cocoyam growing
environment and hence has the potential to greatly increase its cocoyam production.
Women are actively involved in agricultural production in Nigeria, In Sub Saharan
Africa, women grow 80 percent of the food destined to the Kitchen (Mamman, 1994). They
play a variety of roles in agriculture as farmers in their own rights, working in their husbands
farms and are increasing entering employment in the production of all kinds of crops for sale.
Akanji (1999) pointed out that the current state of knowledge is limited due to the under-
reporting of the contributions of women and children to commercial agriculture, this study will
highlight some of the problems confronting especially women farmers, pointing out the
direction for ensuring higher efficiency in farm resource utilization and productivity in their
operations in cocoyam farms.
This study will be essential to understand the nature of the constraints women face in
order to effectively help women farmers because failure to take into account gender relationships
leads to the marginalization of the disadvantaged sector of the society and a large part of the
agricultural work force
It will equally provide the much needed micro level data and the empirical basis for farm
planning, policy formulation and implementation, for no society can afford to neglect the needs,
rights, aspirations and contributions of half of its population. It will ensure policies that will
improve the productivity of male and female cocoyam farmers as well as information on relative
access to and control over resources will be important in the development of food security
strategies.
The study will also provide a basis for equitability, effective and better allocation of
resources between male and female cocoyam farmers. This study will add to the already existing
literature on production which may aid further researchers in other geographical areas. It will also
be useful to potential investors interested in cocoyam business in Anambra state. It can also
provide useful information, which will help in decision making for improvement of cocoyam
business in Nigeria. The study will also be of immense benefits to researchers as well as policy
makers on the need to keep the government at various levels abreast with the economic value of
cocoyam. It is used for teaching purposes. Finally, in the developing countries where technologies
are rarely developed, efficiency is the means of improving production and productivity
CHAPTER TWO
REVIEW OF RELATED LITERATURE
Related literature will be reviewed in this chapter under the following sub headings
� Under Utilization of Cocoyam
� Potentials of Cocoyam
� Gender Issues in Agriculture
� Gender and Farm Input Delivery System, Supply Productivity
� Cost and Return
� Research Problems and Resource Allocation of Rural Economies
� Evidence of Resource Productivity and Efficiency Studies
� Theoretical Framework
� Analytical Framework
2.1 Under Utilization of Cocoyam
Ekwe et al (1999) posits that the reasons for under exploitation of the values of cocoyam
in Nigeria may be attributed to the competition for relevance in the farming and food systems, and
degenerating, unenterprising of the commodity. This has led to the extinction of the crop as a
staple food which is over showed by the new crops, which soon gained ascendancy as a staple
food. The consequence is that the cocoyam becomes grossly marginalized while it rich value
remain underexploited for enhancing household food security and economic empowerment.
The production ccocoyam has not been given priority attention probably due to its
inability earn foreign exchange and its unacceptability to the high income groups for both
consumption and others purposes ( Onyenweaku and Ezeh, 1987). The market demand for
cocoyam is very elastic and by far less than that of its competitors, as a result, its production is
often discouraged by prevailing unfavourable market forces which seriously erode every incentive
to invest in cocoyam production.
According to (Arene and Ene ;1986) the average in daily calories supply of cocoyam was
45.98cal/day which was low compared to 314.8cal/day from cassava and 281.4cal/day from yam
and this data places cocoyam at the periphery of Nigerian diets. Thus cocoyam competes most
unfavourably with these rival crops not only in land areas under cultivation but also in dietary
uses. Nutritionally, the edible corms and cormels of cocoyam contain raphides which are minute
bundles of crystals of calcium exalates which causes irritation to the skin if not well cooked.
Cocoyam also have unattractive mucilage which could discourage consumptions.
Traditionally, cocoyam are consumed by the low income earners and avoided by the high
income and upper social classes. This distinctive attitude earned cocoyam certain socio-cultural
prejudices and untoward perceptions which discourage its production, consumption and choices
as farm business enterprise.
2.2 Potentials of Cocoyam
2.2.1 Nutritive Values of Cocoyam.
Nutritionally, taro and tannia are very similar. Their corms and cormels are composed of
77-86% edible materials and 14-23% scaly peels. These corms and cormels are rich in calcium
phosphate and vitamin A,B and C. Their leaves are very nutritious as they contain up to 20%
protein on a dry weight basis as well as appreciable amount of vitamins and minerals Onwueme
and Sinha, (1991). This agrees with Duru and Uma, (2002)where they stated that in South East
Asia cocoyam leaves are consumed because they are rich in protein and vitamins while the root is
rich in carbohydrates and minerals.
The corms and cormels of cocoyam are rich sources of carbohydrates which provide
energy for man’s physical and mental activities. They also contain protein for body building more
than cassava and yam. Moreover, cocoyam compares favourably with these rival crops and in
some aspects excels in content of such nutrients as protein, vitamin and minerals. In consideration
of these attributes, cocoyam can be fully exploited as a specialist for food resource for the invalid,
babies and nursing mother (Ekwe et al, 1999). Cocoyam has relatively small sized starch grains
which are easily digestible and therefore acclaimed to be very good carbohydrates source for
persons that may be diabetic. This rare attribute is indeed a great value which can be utilized in
management of sugar related diseases that severally occur even among the high income
individuals who ordinarily may not consume cocoyam.
Apart from the corms and cormels the young succulent part of xanthosoma leaves are rich
in thiamine (Arene and Ene;(1987). He also stated that similarly colocasia leaves are rich sources
of folic acid, riboflavin, vitamin A and C, calcium and phosphorus, thus making them
particularly useful for blood and bone build up in the body. The cocoyam leave has great values
for nutritional care of pregnant and nursing mothers.
A beverage made of colocasia powder, sugar, coco milk and salt had been observed to be
a tasteful relish. It is conceived that the colocasia powder could also be a nourishing ingredient in
ice creams and chocolates (Agboola, 1987). Cocoyam also plays very important roles in animal
nutrition, considering the high costs of conventional feeds; use of cocoyam bye-products in local
formulation could significantly reduce cost of livestock production in Nigeria.
2.2.2 Economic Values of Cocoyam
Although cocoyams (taro and tannia) in recent years appear neglected and underutilized
when compared with other food crops, they still maintain important economic values in several
Nigerian households where they are produced for consumption, sales, and planting. In South
Eastern Nigeria cocoyam production and marketing are twin enterprises sustaining the livelihoods
of many rural households.
Specifically, in Anambra and Enugu States rural women invest their resources intensively
for cocoyam production so as to maintain a regular sale of their produce in the local markets or
occasionally at urban markets. This trend also earned the crop a perception as a “women’s crop”.
Income from such sales is used by the women to buy other food stuffs for the household up keep
consumption as well as settle some financial matters. By these practices cocoyam lend substantial
boost and support to the economy of rural households.
Cocoyam still occupies important position in the menus of many low income urban
dwellers. as a result cocoyam marketing enterprises thrive in urban centres. Middlemen travel to
remote rural markets to purchase cocoyam corms and cormels for sale in city markets. The
emergent varied food forms of cocoyam through value addition is also making a big promotion of
cocoyam marketing enterprises, with these value added product like cocoyam soup thickener,
flakes, beverage powder and balls gaining stands in super markets and shops. Cocoyam corms
and cormels have good manageable sizes which make for easy crating and export. Although,
Nigeria is not yet known for cocoyam export, there are unofficial reports that Nigeria cocoyams
are available at African shops in United State of America and Europe (Ekwe et al, 1999).
Industrially, cocoyam can also be useful in boosting the Nigerian economy. It has been
shown that cocoyam starch can be efficiently converted into alcohol which is an essential raw
materials for the manufacture of myriads of products like perfumes fire extinguishes, soaps,
hydraulic fluid, deodorants e.t.c. (Ejiofor, 1987). These products command large domestic and
export markets, yet the potentialities of cocoyam for the products are yet to be fully unlocked in
Nigeria.
Also cocoyam alcohols and starches are required in pharmaceutical and food industries for
production of vitamins, flavours, toothpastes and blood boosting drugs and fortified wines
(Ejiofor, 1987, Okwuowulu et al, 2002), with substantial content of protein, vitamin and minerals
in cocoyam leaves silage could be made from cocoyam leaves and petioles after harvest for use in
livestock feeding.
2.2.3 Agronomic Values of Cocoyam
Cocoyam are early maturing (8-12 months after planting) crops (Uguru, 1996). Although
yield under peasant culture range between 6 to 10 tones per hectare, a yield of 30-60 tonnes per
hectare is attainable if clean healthy and good sized planting materials are used and cultural
practices optimally maintained (Eleje, 1987). Today, even with minimal improvement on the
farmers practice, Nigeria produces about 4 million metric tones per annum which accounts for
40% (largest) of the world production of the commodity (FAO, 2005). Serem et al (2008) pointed
out that cocoyam have also been established to be low maintenance crop that will maintain a
ground cover crop in the field to reduce soil erosion. With potential capacity of 30-40mm/ha
cocoyam, like other tropical root crops has very high propensity for supplying large quantities of
utilizable calories per unit area of land cultivated, (Arene and Ene;1987). Also cocoyam’s
importance as a component of the farming system is easily observed in the rural farm
environments where it is cultivated, sold or in mixture with such crops like yam cassava, plantain,
banana e.t.c. In fact they are more abundantly available in homestead farms than even yam and
cassava.
2.3 Gender Issues in Agriculture
Gender relation refers to social norms and practices that regulate the relationship between
men and women in a given society. Gender relations determine household security, well being of
the family, planning of agricultural production and many other aspects of rural life (Frishmuth,
1997). It is important to understand gender contribution to agricultural production. This
understanding will ensure efficient allocation of scarce resources among competing enterprises in
the household (Onyemauwa et al; 2008). In a Nigerian case study, it was found that women
participated in all aspects of farm work often to an extent as men but decision making concerning
economic activities is mostly the reserve of men, (FAO, 2004). Durno and Stuart (2005) noted
that women produce the bulk of basic food stuffs both for household consumption and for sale,
although it is widely documented that women are more involved in trading and farm food
processing. Several studies have shown a clear departure and a distinctive place of women in all
categories of farm operation. Mkpado and Arene, (2003), and Efifu, (1999) stated that gender
studies in agriculture should analyze the roles and activities of male and females by focusing on
their experience and not on their biological or sex differences in a society. This agrees with
Uzokwe, (2009) that the ability to increase production in developing countries has great gender
implication.
Gender inequality tends to slow economic growth and make the rise from poverty more
difficult World Bank, (2005). It is therefore view the third millennium Development Goals of
promoting gender equality and empowering women as a major central component to its overall
mission of reducing poverty and stimulating economic growth. The current dwindling national
revenue and its economic consequence has put pressure on the male to the extent that women are
no longer permitted to sit at home and adopt the wait-to-be-fed attitude (Ogbosuka & Salahu,
2005). Furthermore Ironkwe et al, (2007) observed that lack of adequate gender specific data and
statistics has given rise to assumption on the contribution of men and women in agricultural
production which negatively influenced agricultural policies, development of improved
agricultural production technology and programmes aimed at increased farm productivity.
Both men and women play critical roles in agriculture throughout the world in producing,
processing and providing the food we eat. FAO (2004) pointed out that women in developing
countries are the main stay of agricultural sectors, the farm labour force and food systems (and
day to day family sustenance), the last to benefit from resources and in some cases have been
negatively affected by prevailing economic growth and development process.
Gender bias and gender blindness persists, policy makers, development planners and
agricultural services deliverers still generally perceive farmers as “male” (Durno and Stuart,
2005) for this reason women find it very difficult than men to gain access to valuable resources
such as land, credit, agricultural inputs, technology, extension training and services that will
enhance their production capacity.
Wieczorec-Zuel (2007) opined that in Sub Sahara Africa, women produce up to 80 percent
of all staple foods, own only 10% of farm land and have little to less than 26 percent of land
across the developing world. According to Verma (2001) women accounted for 70 to 80 percent
of household food production in Sub Saharan Africa, 65 percent in Asia and 45 percent in Latin.
America, and the Caribbean, (FAO, 2004), (Durno and Stuart, 2005) also noted that in South East
Asia, women provide up to 90 percent of labour for rice cultivation. Dimelu et al, (2009) found in
their paper “Determinants of gender efficiency of small holder cocoyam farmers” in Nsukka
agricultural zone of Enugu State, Nigeria, that mean efficiency score for male and female
cocoyam farmers was 20 and 56 percent respectively.
In Sub Saharan Africa women produce up to 80 percent of basic food stuffs both for
consumption and for sale. Women perform from 25 to 45 percent of agricultural field tasks in
Columbia and Peru, women constitute 53 percent of the agricultural labour in Egypt; fewer than
10 percent of women farmers in India, Nepal and Thailand own land, (FAO 2004, Durno and
Stuart 2005).Analysis of credit schemes in five African countries found out that women received
less than 10 percent of the credit awarded to males small holders farmers and only 15 percent of
world’s agricultural extension agents are women (Durno and Stuart 2005). Also FAO (2004)
found out that both men and women in most developing countries do not have access to adequate
resources but women’s access is even more constrained as a result of cultural, traditional and
sociological factors.
There is apparently no strict dichotomy of gender specific crops but it has noted that men
grow more yams and tree crops while women produce cassava, cocoyam, vegetables (Efiful,
1999). Chinaka and Emerole (2006) also conducted a study involving 300 females who were yam
producers in Imo State Similarly Okoye and Onyenweaku (2006) have demonstrated that 74
percent and 26 percent of cocoyam producers in Anambra state were females and males
respectively. Accurate information about men and women’s relative access to and control over
resources is crucial in the development of food security strategies. Rural women form the most
important of majority of the developing nations. In India for example, there are 75 million women
engaged in dairying, 20 million in animal husbandry as compared to 1.5 million men (DAC,
2004). This justifies FAO (2004) recognition that the empowerment of women is key to raising
level of nutrition, improving the production and distribution of food and agricultural products and
enhancing the living conditions of the rural population.
2.4 Gender and Farm Input Delivery System, Supply And Productivity
The adequacy and timeliness of agricultural input supply affects the productivity of farm
enterprises. Farm inputs encompasses among others setts, fertilizers and agro chemicals, cropping
patterns, effective credit institutions, soil and water conservation, irrigation investments as well as
appropriate marketing and price structures and other basic agricultural support services. Mejeha
and Obunadike (1998), in their study on the impact of credit on adoption of innovations on
fertilizer use, yam minisett and cassava in Anambra state of Nigeria found out that farmers spent
more on innovation adoption with credit than without credit, the reason being that credit
availability afforded farmers the opportunity for more access to farm inputs. Their result showed a
positive correlation between credit and innovation adoption. They noted that the rate of adoption
of new technology by farmers is generally high if the profitability of a change over to the new
technology, the economic position of the farmer and the effectiveness of the extension agents are
high.
Nwaru (2004) emphasized that credit provision should be with the supportive services
needed to make the credit facilities work. Short term and long term credit is needed to pay for
inputs and hired labour. However, in the developing world, banks and credit associations are less
inclined to lend to women because without property and land rights, they lack collateral. These
improved inputs such as fertilizers and pesticides are vital means of enhancing production but
extension services and cooperatives distributing inputs rarely reach women who also lack the
necessary cash to purchase even government subsidized inputs. FAO (2005a) reported that few
extension services were targeted to rural women, few of the worlds extension agents were women
and most of the extension services focused on commercial rather than subsistence crops- the
primary concern of women.
FAO (2004) reported that extension is often biased towards cash crops that tend to be
grown by men and large scale farmers. Most programmes targeted towards women tend to focus
on home economics and nutrition rather than farm production and processing. Women are under
represented and sometimes not represented at all among extension staff and trainer, therefore,
there is need for an effective and efficient extension delivery system. In addition, credit should be
made available to small scale farmers especially women. As Desai and Meller (1993) correctly
noted farm level credit, when extended properly, not only for crop farming but for dairying and
other directly related farm level economic activities encourages diversified agriculture which
stabilizes and perhaps increases resources productivity, agricultural production, value added and
net income of farmers, credit availability stirs up farmers, latent entrepreneurship qualities and
that credit equality constitutes the key to unlock the farmers latent vision, talents, abilities and
opportunities that in turn act as the mover of economic progress (Nwaru, 2004). Moreover,
Krause et al (1990) and Immink and Alarcon (1993) noted that lack of access to credit prohibits
smallholder farmers from assuming risks of financial leverage associated with the adoption of
new technology and that lack of access to market reduces gross margins. They reported that
adoption of new technology was also found to be sensitive to the amount of equity capital.
Though access to credit offers liquidity there is usually no rural financial intermediation by
formal credit institutions.
High cost of intermediation is disposed and thin rural market lack of acceptable collateral
and high default rate inhibit the extension of the services of formal credit institutions (Nwaru,
2004). The innovative strategies are required to reduce the cost of rural financial intermediation
which provides small-scale farmers with credit, and facilitates successful technological change
and enhances productivity. This could be through risk sharing schemes between farmers and their
partners, the spreading of credit over farm and non-farm activities that can help farmers build up
their own liquidity and the linking of formal and informal local credit/saving associations.
Ownership of land has a significant bearing on resource use and productivity and that the
divergence between existing and optimal net returns clearly demonstrates the scope of increasing
net returns through optimal and reallocation of resources on owner-cum-tenant and pure tenant
farmers.
2.5 Cost and Returns
Cost: Agricultural production decisions cannot hold without cost considerations Arene (2008).
Cost refers to the value of inputs used in production and the cost of producing commodity such as
cocoyam refers to the expenses incurred in producing a particular quantity of the commodity in a
given period of time. Olayide and Heady, (1982) defined cost as the change in equity caused by
the performances of some special operations. Cost concepts are of great importance as they enable
the farmer to make choices among present alternative actions. Types of costs include;
a) Variable cost: This refers to operating cost and they vary in direct proportion to the level of
activity and include costs of land clearing, cultivation, setts, fertilizer and weeding.
b) Fixed cost: They are the expenses that cannot be changed or altered in the short run (Oji
2002,) fixed cost items include implement action such as machetes, wheel barrow e.t.c. According
to Upton (1996)`, Agom and Idiong (2002) developing countries do not necessarily incure explicit
fixed cost. It is expected that farmer net return will equate the gross margin. If increase in gross
margin can be achieved with existing supply of fixed resources (often the case in rural agricultural
production, profit will be raised by the same amount as the gross margin (Upton, 1996). Hence
the gross margin represents profit and net farm income of the enterprise under this condition.
c) Total cost: This is derived from the summation of variable costs and fixed costs. Total cost
of production is an important parameter in estimating the net profit associated with a given
enterprise.
Returns: This is the revenue, income that is received from the sale of farm output (Olayide &
Heady 1982). The net profit therefore, is given by total revenue less total cost.
2.6 Resource Problems and Resource Allocation of Rural Economies
2.6.1 Resource Problems
Farm resources are inputs of labour, capital, land and management. These inputs are
combined in various ways to produce outputs. Olayide and Heady (1982) refer productivity as the
index of the ratio of the value of the total farm output to the value of total inputs used in
production, they also stated that maximum resource productivity implies obtaining the maximum
possible output from the minimum possible set of inputs. Thus optimal productivity of a resource
denotes an efficient use of the resources in the production process, subject to constraints.
Olayide and Heady (1982) noted that the kinds and quantities of resources used in primary
production activities are characterized by old techniques and simplicity of farms that tend to give
rise to low output. These low outputs results in low food supply and subsequent food and
nutritional, problems which are manifested in subsequent malnutrition disease and socio-political
economic discontent.
Total resource productivity in agriculture is estimated to have grown by an average of 1.3
percent annually between 1961 and 1991 for Africa as a whole. Land productivity rose by an
average of 1.9 percent per year. By contrast, labour productivity fell by an average of 1 percent
per year. Meanwhile growth in agricultural productivity appears to be slowing and land
degradation has been blamed as contributing factor. Moreover, the main problem of resource use
centres on scarcity. This raises the fundamental need for “economizing” productive resources,
consumption goods, money, time and energy in any eco-system. These resources are
characterized by three set of conditions viz scarcity interpreted to mean a situation whereby
people want more of it or of the thing it can help to produce than is freely available, alternative
uses to which the resources can be put and finally its transferability which implies possibility of
movement from one individual or use to another Olayide and Heady (1982).
The available resources, there have not been effective and efficient utilization as in most
cases, they are either under utilized or over utilized (Effiong and Nwaru, 2002, Nwaru, 2002,
2003). Effiong and Nwaru (2002) pointed out that the hub of efficient resource husbandry is the
manipulation of available scarce resources and technical know-how to achieve the possible
highest benefits within given natural and socio-economic environment. Nwaru (2001) noted that
rural resource users must come to a dynamic and innovative level where they can create, establish
and nurse economic activities with greater success through mobilizing and allocating available
rural resources more efficiently. He also pointed out that this will help them conquer the myriads
of constraints and be released from the ugly vicious web of low output, poor income unimproved
inputs and technology leading to low level entrepreneurship. The rural farmers are severely
limited in many respects and the limitations include labour, technical constraints including
inadequate infrastructure dependence on unimproved inputs and rudiment technology (Njoku
1988).
2.6.2 Rural Resource Allocation
Hardwick et al (1994) noted that all methods, resource allocation have social welfare
maximization as their over-riding aim and resource allocation involves decoding what, how and
for whom to produce. According to Upton (1996), traditionally village society is often
characterized as a rural self-sufficient community of people linked through kingship and other
ties. Production distribution and consumption takes place within the closed community while
social and economic relations are based on the status of the individual members. There is strict
observance of social norms and customs including religious beliefs and practices. These
established customs laws and relationships make up the traditional institutions, which governs the
allocation and use of resources and the distribution of agricultural products, which are geared to
securing a minimum level of subsistence for all community members.
Markets have provided opportunities for specialization and division of labour with each
type of farming zone concentrating on those areas for which it has the greatest comparative
advantage. Barau et al (1999) opined that the measurement of output was the first major element
of productivity analysis, since the objective of productivity measurement was to find out how to
produce outputs of desired goods and services with minimum amount of human and physical or
natural resources. Olagoke (1990) emphasized that the problem of low productivity was the
inability of farmers to efficiently make use of available resources. It implies that the problem of
low productivity can be solved if the farmers are exposed to various input combinations, which
may enable the enable the efficient management of resources with the view of increasing output.
Specialization will lead wider choice range of consumer good for rural households, the use
of manufactured chemical, equipment and other inputs from outside system, easier movement of
labour and other resources between regions and greater opportunities for the accumulation of
capital (Adeniyi,1998; Upton, 1996). This on overall should allow increases in production
efficiency, increased income for farm households and a general improvement in social welfare.
Hardwick (1994) opined that market economy will rely on prices as signals to consumers and
producers and the consumer express their preferences for goods and services to producers through
their spending decision viewed as “money vote”. The more money is spent on a particular good,
the greater will be the incentive or producers to supply that good. Farmers allocate their resources
to those productive ventures that earn higher returns for their resources. These resources are
allocated bearing in mind the opportunity cost of allocating them in a particular area. The
quantities of resources used are largely the result of conscious human decisions. More so, for
crops to be produced at optimum profit, variable factors of production should be employed at
levels such that the value of the marginal product is equal to the factor price of each variable
factor. Some inputs are fixed at different levels in different farms such as land supply, the family
size and managerial ability of the farmer. Alternatively, there may be variations between farm in
the price paid by them for resources.
However, inputs according to Upton (1996) do not vary at random between farm firms but
are chosen by farmers or allocated by the society according to some set of decision rules such as
customary rights and traditions. Therefore efficient manipulation of productive resources in the
rural economy of Nigeria can increase output and incomes of farmers for instance, inefficiency in
resource allocation and use has been reported by Effiong and Nwaru (2002) and Nwaru (2003).
This implies that there is room for increasing the current level of food production through a more
efficient use of available agricultural resources.
2.7 Evidence of Resource Productivity and Efficiency Studies
Resource productivity is the quantity of good or service (outcome) that is obtained through
expenditure of unit resources (Hargroves and Smith, 2005). Resource productivity and resource
efficiency are two concepts closely tied to production function. They concern the relative
performance of resources used in production process Eze (2008). Ogundari et al (2004) in the
study of impact of economies of scale and cost efficiency in small scale, resource poor farmer are
efficient in their use of resoures and the expansion of their level of expansion will reduce cost per
output. This is in accordance with result from earlier study of Yotopolus and Lau (1973) where
they indicate higher relative efficiency for small farmers.
In a study on “Rural credit markets and resource use in Arable crop production, in Imo
state of Nigeria, Nwaru (2004) found out that none of the defined farmer groups (credit users and
non credit users) achieved absolute allocatve efficiency because non achieved an allocative
efficiency index of unity. The credit user farmers achieved better allocative efficiency than non-
credit users in the use of material inputs and capital while the non credit users are better in
allocating farmland. While the credit user farmers over utilized hired labour, capital, material
inputs and fertilizer and underutilized farmland the non credit users farmers over utilized hired
labour, family labour and capital and underutilized farmland and material inputs.
Nwaru and Ekumankama (2002) studied the economics of resource use by women arable
farmers in Abia state and found out that on the average, men cultivated 2.15 hectares and women
1.47 hectares and that the women farmers were allocatively more efficient in the use of fertilizer
and capital while men performed better in the use of labour, other inputs and farm land. Nwagbo
and Onwuchekwa (1998) found out that hired labour contributed to low productivity due to high
labour hiring rate in farm operations. Family labour is the most important source of farm labour in
Nigeria and is influenced by household size farm size, composition of household among others
(Okoye 1989). This agrees with Chidebelu (1990) where he noted that family is the most
important input of unpaid labour.
Ohajianya and Onyenweaku (2001) using profit function approach, found equal economic
efficiency between small scale and large scale farmers in the swamp rice production system in
Ebonyi state of Nigeria. Also in their earlier study of gender and relative efficiency in rice
production system in Ebonyi state of Nigeia, Ohajianya and Onyenweaku (2001), using profit
function approach observed no significant difference in economic efficiency between male and
female farmers in swamp and upland rice production systems.
Alabi and Aruna (2006) studied the technical efficiency of family poultry production in
Niger Delta, Nigeria, it was discovered that inefficiency parameters show age as being negatively
related to poultry production. It further showed that family size, gender, innovation adoption have
negative relationship with efficiency of poultry production.Ogar et al (2002) while studying the
allocative efficiency of labour resources in swamp rice in Obudu, Cross River state of Nigeria
found inefficient allocation of labour during clearing and weeding operation among rice farmers
in the area.
Onyenweaku and Ohajianya (2005) measured the level of technical efficiency of upland
and swamp rice farms in South Eastern Nigeria using stochastic frontier production function.
They noted that the estimated farm level technical efficiency ranges from 28.19 percent to 93.13
percent with a mean of 63.87 percent for swamp fields and from 17.19 percent to 92.15 percent
with a mean of 65.24 percent for the upland fields they concluded that wide variation in technical
efficiency in the production system shows that ample opportunities exists for rice farmers to
increase their productivity and income through improvements in technical efficiency.
A study by Ajibefun and Abukadri (2004) on impact of farm size operation on resource
use efficiency in small scale farming shows that resources availability does not translate into
efficiency. In the study, it was discovered that farmers with less intensive use of land, labour and
capital resources are efficient in the use of the resources than farmers that use resources
intensively. A study by Awudu and Huffman (2000) on economic efficiency of rice farmers in
northern Ghana shows that 29 percent of potential maximum profit was lost due to inefficiency.
The study further shows that high level of education reduced profit inefficiency.
2.8 Theoretical Framework
A theory is a set of related statements that are arranged so as to give functional meaning to
a set of events. The basic theories on which this work could be based are theories of resource use,
production and efficiency. This work could also be underpinned in one or more hypotheses
relating to gender and agricultural production. Farm resources are inputs of labour, capital, land
and management. These inputs are combined in various ways to produce some output. A resource
is any good or services which has the capability of satisfying human wants. It varies with the
qualities of scarcity and value and therefore choices must be made about the use to which a
resource will be put. Onyemauwa et al (2008) content that resource use refers to allocation of all
resources between competing alternative with aim of deriving maximum returns such as profit,
food calories or national income from given resources. Production of farm commodities like
cocoyam involves numerous relations between resource inputs and products. it is concerned
essentially with deriving a maximum level such as profit food calories or national income from
given resources, and products is very important because it provides the tools by which the
problems of productions and resource use can be analysed.
Production refers to the principles to be applied in making production decisions (Oji
2002). Production decisions include the decision include the decision to acquire resources, utilize
resources, organise production, distribute the product of the productive activity and in general to
manage the services of production resources. Therefore, production is the process whereby some
goods and service whereby some goods and services called inputs are transformed into other
goods and services called output. Production function refers to the technical relationship which
connect factor inputs with outputs in a production process (Oji, 2002). The production function
could be expressed in the implicit form as:
Y = +(x1, x2, x3 ……. xn) . . . . . . .(2.1)
Where: Y is the output or the product level inputs and xi = (1 are the resource levels. Nwaru
(1993) noted that production function has no part in choice or decisions making in investment as
it seldom defined which production pattern or resource use is the best level. He noted that the
most desirable combination of factors or production could only be determined when economic
principles are applied. This application moves agricultural production from the fields of biological
science to the field of economics (Nwaru, 2004) Equation (2.1) gives the total physical product
(TPP). A number of production parameters can be derived from this production function. they
include average physical product (APP), Marginal Physical Product (MPP), Elasticity of
Production (EP) and return to scale. Onyebinama (2000), Oji (2002) and Hendersen and Quandnt
(2003) described this parameter.
In Agriculture, there are marked and persistent gender inequalities mostly in cocoyam
production. Concept of gender often enters discussion within agricultural development either
through distinctions between male and female headed households or through distinction between
men and women roles in farm activities (Doss, 2002). This distinction affects the resource use
efficiency and the output of cocoyam. Gender bias influences resource allocation between men
and women, attitudinal barriers against women are deeply rooted in patriarchy based socialization
where men are considered more superior to women in socio economic activities and low women
presence in decision making bodies (Amaechina 2002). if women should become more and well
equipped as well as male with needed skills and financial capacity to be more relevant in farm
resource allocation and decision making the output and productivity of cocoyam will increase in
the study area.
Efficiency is central to economic analysis because it provides the yard stick for evaluating
decisions on choices regarding the use of scarce resources. If these resources (land, labour, capital
and management) are not efficiently utilized low productivity and waste results. The crucial role
of efficiency in increasing agricultural output has been widely recognized by researchers and
policy makers alike. Thiam et al, (2001) highlighted the importance of efficiency as a means of
fostering production which has led to proliferation of studies in agriculture on technical efficiency
around the globe micro economic production function studies have usually been used as tools for
examining problems of efficiency of resource use and productivity at farm enterprise level. This
study is based on the theory of resource use efficiency to maximize cocoyam output per hectare of
land area by gender, therefore, the problem of low productivity of agriculture can be solved by
improving efficiency of resources used (Ojo, 2003). Firms lying on the production frontier are
100 percent technically efficient with (T.E. = 1) and Technical inefficiency of the firm increases
with distance from the production frontier (Forsund et al 1990 in Ugwu 2008).
Technical Efficiency:
Technical efficiency in production is ability of the farmer to produce at the maximum output
frontier production given quantities of inputs and production technology (Amaza and
Maurice,2005). The definition of technical efficiency implies that differences in technical
efficiency between firms exists. Variation in technical efficiency of producers might arise from
managerial decisions and specific-farm characteristics that affect the ability of the producer to
adequately use the technology. In Farrell’s(1957) concept, the overall efficiency (O.E) is a
multiplicative combination of technical(TE) and allocative efficiency(AE) i.e OE=TE & AE.
Technical efficiency is the ability to produce a level of output with minimum quantity of inputs
under a certain technology. It is a micro concept observed differentials in technical efficiencies
which may be due to differences in managerial ability, the presence of different environmental
conditions such as soil quantity,rainfall,temperature,soil radiation, precipitation e.t.c non technical
and non economic factors which can prevent the user of the resources from working so hard
enough, thus failing to achieve the best level of output such as sickness (Nwaru,1993,2004).
Ogundele (2008) maintained that technical efficiency of a farm are characterized by relationship
between production or efficient production frontier. Omotosho et al (2008) stated that technical
inefficiency arises when actual or observed output from a given input is less than that of the
maximum possible. This agrees with Kadurumba et al (2010) when they found out that technical
inefficiency exists among palm oil farmers in Imo state.Onyenweaku and Nwaru (2005) used the
application of stochastic frontier production in the measurement of technical efficiency in food
crops in Imo State,Nigeria.
According to Nwakolobo (2000), a farmer who is said to be technically efficiently
produces as much output as possible from a given set of inputs or if he uses the smallest possible
amount of inputs for a given level of output. Technical efficiency is thus calculated as Technical
efficiency = actual output/ potential output. However,several other methods of research
philosophical view of importance of measurement error (Forsund et al 1980 in Ugwu 2007).The
various methods calculate a technical efficiency index ( TESCORE) which measure the distance
of the observed firm from a point on the production frontier (Brock et al;2006). Firms lying on
the production frontier are 100 percent technically efficient with (T.E=1) and technically
inefficiency of the farm increases with distance from the production frontier (Forsund et al 1990
in Ugwu 2008)
Allocative Efficiency:- Allocative efficiency has to do with the extent to which farmers
make decision by using inputs up to the level at which the marginal value product (MVP)equal to
the Marginal Factor Cost (MFC). Allocative efficiency measures the extent to which an analyzed
Diminishing Marginal Utility (DMU) produces its outputs in a production that minimizes cost of
production, assuming that the unit is already fully technical efficient i.e. when allcoative is pareto
efficient. A firm therefore is considered allocatively efficient in the use of a production resources
if the farm is able to equate the value of the marginal value product (MVP) of the factor to that of
factor price is able to maximize profit with respect to that factor.
Economic Efficiency: Economic efficiency is the ability of a firm to maximize profit. It is also
known as production efficiency and it is described as the product of technical and allocative
efficiencies. An economically efficient input/output combination would be both on the frontier
and the expansion path way (Ogundari and Ojo; 2006). Economic efficiency exists when the
MVP is not significantly different from MFC. (MVP = MFC). To achieve economic efficiency,
the ratio of MVP to MFC must be equal to one. Economic efficiency is concerned with maximum
profit. That is when a firm chooses resources in such a way that its marginal value product is
sufficient to offset marginal cost. The MVP is calculated from the respective regression
coefficients using appropriate optimum levels of output price depending on the lead equation of
the functional forms. The MFC is the market price of one unit of input. A ratio of less than one
implies that input is being over utilized while a ratio greater than one implies that input is under
utilized (Onojah 2004; Haruna et a;l 2008).
A study by (Egwu et al; 2010) on a Technical Efficiency of commercial vegetable
production in Akwa Ibom State, Nigeria. The estimated results shows that technical efficiency of
the farms varied between 0.71 – 0.99 with mean technical efficiency of 0.86 implying average
technical efficiency as 81.7% of the difference between observed and best practical output among
the sampled farms was explained by technical inefficiencies.
A study carried out by (Anyaegbuna et al; 2009) on a translog stochastic cost inefficiency
among small holder cassava farmers in South East agricultural zone of Nigeria. The parameter of
the stochastic frontier cost function were estimated using the maximum likelihood method. The
result of the analysis shows that individual farm level cost efficiency was about 69%. A study
carried out by (Ndukwu et al; 2010) on gender and relative economic efficiency in sweet potatoe
farms of Imo State, Nigeria. A stochastic cost frontier approach. The result of the analysis showed
that the mean economic efficiency for the female farmers group was higher 82% than the male
71% counterpart.
2.9 Analytical Framework
Production efficiency is concerned with the relative performance of the process used in
transforming inputs into output (Arene, 2003, Eze, 2008). The four major methods used in
efficiency and productivity measurement are Least Square Econometric Production Models
(LSEPM), Total Factor Productivity Indices (TFPI), Data Envelopment Analysis (DEA) and
Stochastic Frontier Production Function (SFPF) analysis Ogundari (2006). Eze (2008) reported
that Stochastic Frontier Production Function (SFPF) analysis and Data Envelopment Analysis
(DEA) became the most commonly used methods. Both methods estimate the efficiency Frontier,
which shows the best performance observed among firms. The major reason why Stochastic
Frontier Production Function (SFPF) is commonly used is that it takes into account measurement
errors and other noise in the data, previous research on Stochastic Frontier Production Function
(SFPF) include Battesse and Coelli (1995), Amaza P. S. & Maurice (2008), Kadurumba (2010).
In this study, the Stochastic Frontier Production Function will be used for the analysis.
The Stochastic Frontier Production Function (SFPF) as defined by Coelli (1996) is specified as:
Y: = F (xi;β)exp (Vi – Ui); : = 1,2, --n -------------------------- (2.1)
Where,
Yi = Denotes output of the ith farm
Xi = is a vector of functions of actual input quantities used by the ith farm
β = is a vector of parameters to be estimated
Vi - Ui = is the composite error term (Aigner et al, 1977, Meeusen and van den Broeck, 1977)
Where,
Vi and Ui = are assumed to be independently and identically distributed
Ui = is a non-negative random variable, associated with technical inefficiency in production.
Vi = is a random error, which is associated with random factors not under the control of farmers.
Technical efficiency of an individual farmer is defined as the ratio of the observed output
to the corresponding frontier output, conditional on the levels of inputs used by the farmer. The
technical efficiency of farmer (i) in the contest of the stochastic production function in equation
(1) is:
TE = Yi/Yi* …………………………………… (2.2)
= F (Xi; β) exp (Vi – Ui)/ F (Xi; β) exp (Vi) …………………………………… (2.3)
= exp (-Ui) ……………………………………. (2.4)
Where,
Yi = is the observed value of output
Yi* = is the frontier output (Potential output)
Given the density function of Ui and Vi the frontier production function will be estimated by
maximum likelihood techniques.
The value of the technical efficiency lies between zero and one. The most efficient farmer
will have value one, while farmer having value lying between zero (0) and one (1) is described as
inefficient.
(b) Allocative Efficiency: This will measured as follows:
AE = EE/TE
Where AE: Allocative Efficiency
EE: Economic Efficiency
TE: Technical Efficiency.
Determinants of Allocative Efficiency will be modeled in terms of socio-economic
variables of cocoyam farmers. The allocative efficiency in the model was simultaneously
estimated with their determinants following kaldJan (1991) Exp. (.vi) = β0 + β1 Y1 + β2 x2 + β3 x3
= … +Σi (2.5)
Where Exp (-u) = efficiency of the ith farmer.
CHAPTER THREE
METHODOLOGY
3.1 STUDY AREA
The study will be carried out in Anambra State. The State is made up of 21 Local
Government Areas. It is located between latitudes 60 45
1 and 5
0 44
1 N and longitudes 6
0 36
1 and
70 20
1 E of the area with meridian. The temperature of the State during the dry seasons,
especially in January, ranges from 25.5 to 30.50C while during the raining season especially in
July it ranges from 25 to 27.50C (ANSEP 2000). The rainfall between November and April ranges
from 250 to 500 millimeters while between May and October it is over 2000 millimeters “(Duze
and Afolabi, 1985)”. The State is divided into four Agricultural zones namely, Aguata, Awka,
Anambra, and Onitsha. The zones are further delineated into 24 extension blocks and 120 circles
(Nkematu, 2000, ANSEP 2000). Anambra State is bounded to the North by Kogi State, to the
South by Imo and Abia States, to the East by Enugu State and to the West by Delta State. The
State, according to the N.P.C. Census figure has a population of 4,185,032 persons distributed as
2.1 million males and 2.1 million females (NPC, 2006).
Yam and cassava-based mixed cropping enterprises dominate small scale farm holdings in
the State besides rice production in Ayamelum, Ogbaru, Anambra East and West Local
Government Areas. Other crops gaining prominence in the area include potatoes and cocoyam
(Okoye and Onyenweaku, 2006). Still other crops grown in the State are maize, okro,
amaranthus, melon, pumpkin, perpes and garden eggs which are intercropped with base crops.
Legumes such as groundnuts and some varieties of cowpea are also cropped. Tree crops grown in
Anambra State include oil palm, mangoes, oranges, oil bean tree and fruits crops like pineapple,
bananas, paw-paw (Ugbajah, 2007).
With respect to animals, sheep and goat production, rabbitory, fish farming and poultry
enterprises are also practiced. Farmers in the State also engage in a wide variety of off farm
activities such as shoe repairing and petty trading on non-farm produce, especially during the off
farm seasons. Farmers dominate the State population hence, food production, processing and
marketing constitutes the major occupation.
3.2 Sampling procedure
Multi-stage sampling techniques will be used in selection of Agricultural Zones, blocks,
circles and contact farmers.
Stage I: Aguata and Awka Agricultural Zones will be purposely selected based on
intensity of cocoyam production (ANSEP, 2000) and two blocks each from each zone.
Stage II: From the selected blocks two (2) circles each will be selected from the blocks
given a total of (eight) 8 circles. From the selected circles, 20 contact farmers (comprising male
and female) will be randomly selected from the circle which will give a total of one hundred and
sixty (160) contact farmers.
Table 3.1: SELECTION OF COCOYAM FARMERS IN THE STUDY AREAS
_____________________________________________________________________
Agricultural zone Blocks Circles Cocoyam farmers
_______________________________________________________________________
Aguata Aguata Ekwulobia 20
Ajali 20
Orumba South Ogboji 20
Ezira 20
Awka Njikoka Nimo 20
Umunachi 20
Dunukofia Ukpo 20
Abagana 20
________________________________________________________________________
2 4 8 160
________________________________________________________________________
3.2 Sampling procedure
Multi-stage sampling technique was used in selecting of Agricultural Zones, blocks,
circles and farmers.
Stage I: Aguata and Awka Agricultural Zones was purposively selected based on intensity
of cocoyam production (ANSEP, 2000) and two blocks each from each zone.
Stage II: From the selected blocks, two (2) circles were selected from each block given a
total of (eight) 8 circles. From the selected circles, 20 farmers were randomly selected from each
circle which gave a total of one hundred and sixty (160) farmers (comprising male and female).
3.3 Data Collection
Both primary and secondary data were used. Secondary information was collected from
relevant literatures, journals and periodicals. Primary data were collected by the researcher
through field survey using structured questionnaire/interview schedule which elicits responses
from cocoyam farmers. Primary data collected include socio-economic characteristics of the
respondents, such as age, sex, household size, educational background, farming experience etc
Others was based on farm inputs like fertilizer, labour use farm size, capital assets, credit and
extension services; cost and returns (input and output) arising from cocoyam production.
3.4 Data Analysis
Objectives (i),and Objective (vi) were realized using descriptive statistical tools like
frequencies, means and percentages
Objective (ii) was analysed using T-test
1
2
2
1
2
1
21
nn
XXt
SS+
−=
−−
X1=The mean technical efficiencies of male cocoyam farmers
X2=The mean technical efficiencies of female cocoyam farmers
S12=The variance of technical efficiency of male cocoyam farmers
S22=The variance of technical efficiency of female cocoyam farmers
n1=The sample size of male of male cocoyam farmers n2= The sample size of female cocoyam
farmers.
Objective (iii) was realized using stochastic production function and multiple regression analysis.
The following functional forms via linear, semi log, exponential and double log forms following
Coelli (1994).The best was chosen based on high R2
values and no of significant factors and
apriori expectations
i) The Cobb-Douglas function
eixlbxlbxlbby nnn +++= 5522110 ......ln
(3.1)
ii) Semi-log function.
y= b0 + bllnx1 + b2lnx2……b5lnx5 + ei (3.2)
(iii) Exponential.
ln y = b0 + b1lnx1 + b2lnx2 …b5lnx5 + ei (3.3)
(iv) Linear function
y = b0 + b1x1 + b2x2 + …b5x5 + ei (3.4)
Where
Y = output of the farm in Kg
qty of fertilizers used in Kg
thi
1x =
X2=capital input (N) made up of depreciation on fixed assets
= Family labour in mandays used in production
X4= farm size measured as total land areas in hectares
X5= qty of cocoyam setts planted in Kg.
= Intercept
= coefficients estimated
ln = represents the natural logarithm.
For technical efficiency;A Cobb Douglas Stochastic Frontier Production Function was also used
through maximum likelihood estimate approach to determine the technical efficiency of the
cocoyam farmers for both gender.
Cobb-Douglas functional form is given by:
ln y = β0 + β1lnx1 + β21nx2 + β3lnx3 + β4lnx4 + β5lnx5 + vi - ui (3.5)
Y = total farm output of cocoyam (kg/ha)
ln = the natural logarithm
β0 – β5 = parameter to be estimated.
= fertilizer (kg)
= capital inputs (N) (depreciation changes on farm machinery, implements and tools,
interest on loan, land rent).
=labour (mandays)
= farm size (ha) other inputs (N) planting materials and other expenses like
=cocoyam sett.
vi = independency and identically distributed random error
ui = Random error associated with technical inefficiency in production.
Farm socio-economical and farm specific factor were determined using.
Exp (-u) = β0 + β1z1 + β2z2 + β3z3 + β4z4 + β5z5 + β6z6 + β7z7 + β8z8 + β9z 9 + vi – ui (3.6)
Where
Exp (-U1) = technical efficiency of the ith farm
Z1 = marital status
Z2 = age of farm in years
Z3 = Household size
Z4 = level of production in years of schooling
3x
oB
isB
1x
2x
3x
4x
5x
Z5 = farming experience in years
Z6 = extension contact (no of times)
Z7 = member of co-operative society
Z8 = farm size
Z9 = Access to credit
Vi = independently and identically distributed error
Ui = random error associated with technical inefficiency in product intercept
β 1 - β 9 = Parameters to be estimated
Allocative efficiency, was determined by equating the marginal value product (MVP) of the ith
input to its price or marginal factor cost (MFC) that is
MVPx1 = Px1 ……… (3.7)
MVPx1 (I = 1,2…….5) = the marginal value product of the ith
input = Py fx
PX1 (i = 1,2 -------- 5) = the marginal value product of the ith
input
Py = unit price of output
According to Okoruwa and Ogundele (2008), for all the resources measured in physical terms, the
allocative efficiency index, Wij, for each farmer type is given
MVPx1 = Pyf1 = Wij
As Px1 Px1 ------------- (3.8)
Where i, is a particular resource, j is the farmer group and all other variable are as previously
defined for any resource that will be measured in monetary or value terms, the unit input price
becomes irrelevant and equation 5 translate to:
MVPx = PyF1 = Wij = (3.9). In this study, the dependent variable y will be measured in
physical terms while other inputs and capital inputs will be measured in value on monetary terms.
Accordingly, the MVP of the resources measured in value terms are directly equal to their
allocative efficiency indices. This is because the marginal value products were already deflated
factor prices since the value of factor are the products of the quantity employed and the unit factor
prices. Maximum or absolute allocative efficiency for a particular farmer group is confirmed with
respect to a given resources. If wij = 1. The resources is over-utilized if Wij < 1 and under-
utilized if Wij > 1.
Returns to scale of the male and female cocoyam farmers was derived through the
summation of the elasticity of production (EP) for the various resources. With the double log
functional form as the lead equations for the men and women cocoyam farmers, the regression
coefficients are directly the elasticity of production.
Objective (v) was realized using cost and return analysis This Gross Margin is given by Gm =
GFI – TVC
Where;
GM = Gross margin (N/ha)
GFI = Gross farm income (N/ha)
TVC = Total variable cost (N/ha)
And Return Per Naira Invested is given by
RNI = TVGM ÷
Where:
GM = Gross Margin
TVC = Total Variable Cost.
3.5 Hypotheses
(1) Age is significant and negatively related to technical efficiency
(2) Marital status, House hold size, Education, Farming Experience, Extension contacts, Co-
operative society, Farm Size and Access to credit are significant and positively related to
technical efficiency.
(3) There is no significant difference in allocative efficiency of the cocoyam farmers in the use of
farm resources by gender.
(4) There is no significant difference in output of cocoyam across gender.
CHAPTER FOUR
RESULTS AND DISCUSSION
4.1 SOCIO-ECONOMIC CHARACTERISTICS OF THE RESPONDENTS BY GENDER.
4.1.1Marital Status
Table 4.1 shows that 74% and 72.93% of the male and female farmers respectively were
married while only 26% and 27.27% of the male and female farmer were single. This implies that
the area was dominated by cocoyam farmers who were married.
4.1.2Age
Table 4.1 indicates that only 8% and 8.18% of the male and female farmers were less than
31 years of age. Further results showed that 46% and 60.35% of the male and female farmers fell
within the age range of 31-50yrs. Also 46% and 26.36% of the male female farmers were more
than 50yrs of age. This implies that the study area was dominated by farmers who are still in their
most productive years, strong and agile. Nwaru (2004), Ndukwu et al (2010) and Dimelu et al
(2009) found out that the ability of a farmer to bear risk, be innovative and be able to do manual
work decreased with age.
4.1.3 House Hold Size
Table 4.1 depicts that 40% and 62.73% of the male and female farmers respectively had
households of 1-5 persons while 52% and 37.27% of the male and female farmers respectively
had households of 6-10 persons. Only 2% of the male farmers had households greater than 10
persons. Effiong (2005), Idiong (2005) and Dimelu et al (2009) reported that a relatively large
household size enhanced the availability of labour.
4.1.4 Education
Table 4.1 shows that only 4% and 4.54% of the male and female farmers respectively had
no form of formal schooling. The result also show that 54% and 45.45% of the male and female
farmers respectively attended primary level of education. About 38% and 46.34% of the male and
female farmers respectively attended secondary level education. Only 4% and 3.64% of the male
and female farmers respectively attended tertiary level of education. The finding indicates that
relatively literate farmers dominated the study area. Educated farmers are expected to be more
receptive to improved farming techniques, while farmers with low level of education or without
education would be less receptive to improved farming techniques (Okoye et al; 2007;Okoye and
Onyenweaku, 2007 and Ajibefun and Aderinola, 2004).
4.1.5 Farming Experience
The data in table 4.1 shows that only 18% and 13.64% of the male and female farmers
respectively had 1-5years of farming experience. Also the results showed that 48% and 51.81% of
the male and female farmers had between 6-15yrs of farming experience each. Further studies
showed that 34% and 34.54% of the male and female farmers respectively had more than 15yrs of
farming experience. This implies that the study area was dominated by experienced farmers.
Nwaru, (1993), Dimelu et al (2009) and Okoye et al (2008) reported that farmers count more on
their experience than educational attainment in order to increase in their productivity.
4.1.6 Extension Contact
The data in table 4.1 shows that 20% and 18.18% of the male and female farmers
respectively had no form of contact with extension. More so 62% and 66.35% of the male and
female farmers respectively had 1-4 number of extension contacts. Further studies indicated that
4% and 2.73% of the male and female farmers had respectively had 5-6 number of extension
contacts while 6% and 12.73% had more than 6 extension contacts for the male and female
farmers respectively. Good extension programmers and contacts with producers are key factor in
technology dissemination and adoption (Bonabana-Wabbi, 2002).
4.1.7 Membership of Cooperatives
The data in table 4.1 indicates that 52% of the farmers belonged in one form of social
organization or the other while 48% of male did not. The implication of the result is that the
females are likely to have more access to agriculture, information and production input
(Onyenwaku and Nwaru 2005). Acquisition of information about a new technology demystifies it
and makes it more available to farmers (Bonabana-wabbi, 2002). Information reduces the
uncertainty about technology’s performance hence may change individual’s assessment from
purely subjective to objective over time
4.1.8 Farm Size
The data in table 4.1 showed that 86% and 74.54% of the male and female farmers
respectively owned between 0.1-0.6ha of land. The results also show that 14% and 25.45% of the
male and female farmers respectively owned between 0.7-1 ha of land. This implies that the areas
were dominated by small-holder farmer. Farm size can also encourage farmers to intensify
agricultural production.Hazarika and Subramanian (1999) are of the opinion that if farm size is
small, farmers are able to combine their resources better.
4.1.9 Income.
The result in table 4.1 showed that 4% and 5.45% of the male and female farmers
respectively had an income less than N21,000. Further results showed that 24% and 27% of the
male and female farmers respectively also had between N21,000 – N40,000 only, The result also
shows that 4%, 28% and 10% of the male farmers had between N41,000 – N60,000, N61,000 –
N80,000 and N81,000 – N100,000 respectively in the study area. The result also shows that
2.73%, 25.45% and 33.64% of the female farmers had between N41, 000 – N60, 000, N61, 000 –
N80, 000 and N81, 000 – N100, 000 respectively. The high income cocoyam production by the
female farmers may be as a result of the years of experience spent in cocoyam production. This is
in consonance with Okoye et al (2008) who have similar view.
Table 4.1: Distribution of Male and Female Cocoyam Farmers According to Socio-Economics
Characteristics. ______________________________________________________________________
Male Female ________________________________________________________________________
Variable Frequency Percentage Frequency percentage
________________________________________________________________________
Marital status
Married 37 26.00 80 72.73
Single 14 74.00 30 27.27
________________________________________________________________________
Total 50 100.00 110 100.00
Mean 0.74 0.73
________________________________________________________________________
Age
< 31 04 08.00 08 8.18
31-40 07 14.00 27 24.45
41-50 16 32.00 45 40.90
51-60 08 18.00 17 15.45
>60 14 28.00 12 10.95
________________________________________________________________________
Total 50 100.00 110 100.00
Mean 50.94 46.16
________________________________________________________________________
Family Size
1-5 23 46.00 69 62.73
6-10 26 52.00 41 37.27
>10 01 2.00 - -
________________________________________________________________________
Total 50 100.00 110 100.00
Mean 5.38 4.98
________________________________________________________________________
Education
No Schooling 02 4.00 05 4.54
Primary 27 54.00 50 45.45
Secondary 19 38.00 51 46.34
Tertiary 02 4.00 04 3.64
________________________________________________________________________
Total 50 100.00 110 100.00
Mean 7.68 7.40
_________________________________________________________________________
Farming Exp. 1-5 yrs 09 18.00 15 13.64
6-10 yrs 20 40.00 40 36.36
11-15 yrs 04 8.00 17 15.45
>15 yrs 17 34.00 38 34.54
________________________________________________________________________
Total 50 100.00 110 100.00
Mean 14.08 13.51
________________________________________________________________________
Ext Contact None 14 28 20 18.18
1-2 21 42 56 50.90
3-4 10 20 17 15.45
5-6 02 4 03 2.73
>6 03 6 14 12.73
__________________________________________________________________________
Total 50 100.00 110 100.00
Mean 2.14 3.35
__________________________________________________________________________
Cooperative Yes 26 52 54 49.09
No 24 48.00 56 50.91
____________________________________________________________________________
Total 50 100.00 110 100.00
Mean 0.52 0.49 _____________________________________________________________________________
Farm Size(ha) 0.1-03 13 26.00 21 19.09
0.4-06 30 60.00 61 55.45
0.7-0.9 05 10.00 16 14.54
1ha 02 4.00 12 10.91
______________________________________________________________________________
Total 50 100.00 110 100.00
Mean 0.49 0.54
______________________________________________________________________________
Income(N)
<21,000 02 4.00 06 5.45
21,000-40,000 12 24.00 19 17.27
41,000-60,000 02 4.00 03 2.73
61,000-80,000 14 28.00 28 25.45
81,000-100,000 19 10.00 37 33.64
______________________________________________________________________________ Total 50 100.00 110 100.00
Mean 72,430 83,100
________________________________________________________________________________________________
Source; Field Survey, 2011
4.2 COMPARISON OF MEAN OUTPUT OF MALE AND FEMALE COCOYAM FARMERS.
Table 4.2. shows that the mean outputs of male and female farmers were 2,450.2kg and
2519.091kg respectively. The mean output of the female cocoyam farmers was higher than that of
their male counterparts. This could be as a result of their higher experience in cocoyam
production. A t-value of -0.4065 indicates that there is no significant differences between the
male and female cocoyam outputs in the study area. Therefore policies that would enable the
women to remain in cocoyam production should be put in place. Such policies should equally
enable the male farmers to improve on their productivity .
Table 4.2. Two sample T-test of cocoyam output by gender
________________________________________________________________________
Variable Obs Mean output/kg Std.Error Std Devi t P> t
______________________________________________________________________
Men 50 2450.2 129.1907 913.5164 -0.4065 0.6849
Women 110 2519.091 97.9770 1027.6
_________________________________________________________________________
Source field survey, 2011
4.3 ESTIMATION OF TECHNICAL AND ALLOCATIVE EFFICIENCY IN COCOYAM PRODUCTION.
4.3.1 Technical Efficiency
Table 4.3 shows the maximum likelihood estimates of the stochastic production frontier
function for male and female farmers in Anambra State. The coefficients for fertilizer were
positive and significant at 10% and 5% levels of probability for the male and female farmers
respectively. The coefficients of cocoyam setts were also positive and significant at 5% and 1%
levels of probability for the male and female farmers respectively. The results also showed that
the coefficients for labour were positive and significant at 10% level of probability for the male
and female farmers respectively. The coefficient for capital input was also positive and significant
at 1% level of probability for the male farmers only while the coefficient was not significant for
the female counterparts. These results are expected and in accordance with apriori expectation.
Any increase in these variables will lead to a corresponding increase in cocoyam output. The
coefficients for farm size were positive but not significant. This goes contrary to (Kaldjian, 2001)
who stated that small farmers “ having all ones land in a single soil type, in a small location and
single exposure is considered risky. The coefficient for extension contacts for both gender were
not significant and negative too. The coefficient for membership of cooperatives for both gender
were not significant but negative and positive for male and female cocoyam farmers respectively.
The coefficient for Access to credit was not significant but negative and positive for the male and
female cocoyam farmers respectively. The estimated variance (r2 ) was statistically significant at
10% and 1% levels of probability for the male and female farmers respectively. This indicates
goodness of fit. The gamma (γ) is estimated at 0.77 and 0.97 for the male and female farmers
respectively and is significant at 5% and 1% level of significant respectively. This indicates that
77%and 97% of the total variation in cocoyam output for the male and female farmers
respectively was due to technical inefficiencies.
Table 4.3: Maximum Likelihood Estimates of the Cobb-Douglas Stochastic Production function for
male and female farmers in Anambra State. ______________________________________________________________________________________
_____________________________________________________________________________________________________
Source: computed from frontier 4.1 MLS/survey data 2011 *,**,***, is significant at 10%,5%,1% level of significance
Figures in parenthesis are t - values
Production Factors _________________________________________
Parameter ____________
Coefficient
_____________________________________
Males Females Constant term Β0 8.6229
(7.4599)***
6.6324
(12.3883)***
Fertilizer used(kg) Β1 0.2159
(2.5366)**
0.1589
(2.5352)**
Capital(N) Β2 0.3704
(4.1169)***
0.0264
(0.5182)
Labour (mandays) Β3 0.1309
(7.2523)***
0.4288
(11.4957)***
Farm size(Ha) Β4 0.2332
(1.4143)
-0.0942
(-0.7822)
Cocoyam sett (kg) Β5 0.0425
(2.6354)**
0.0511
(4.3486)***
Efficiency factors
Constant term Z0 2.5064
(1.8274)*
-0.3649
(-0.4879)
Marital status Z1 -0.0373
(-1.0209)
0.0236
(1.2930)
Age(yrs) Z2 -0.0579
(-1.7091)*
-0.0374
(-1.8416)***
Household size Z3 0.1940
(1.8615)*
0.0226
(1.2401)
Education(yrs) Z4 0.0362
(2.8928)**
0.03098
(3.0303)***
Farming experience (yrs) Z5 0.0332
(6.9864)***
0.0537
(3.6457)***
Extension Contacts(Nos) Z6 -1.0072
(-0.8209)
-0.0070
(-0.4113)
Membership of coop Soc Z7 -0.0016
(-0.0030)
0.2047
(0.5505)
Farm Size Z8 -0.0369
(-2.5783)**
-0.5505
(-3.2829)***
Access to Credit
Z9
-0.2406
(-0.7997)
0.1864
(0.5772)
Sigma squared Γ2 0.3169
(2.0387)*
0.6044
(4.8789)***
Gamma Γ 0.7752
(2.8361)**
0.9733
(51.3708)
Log likelihood function N -30.4007 18.7118
4.3.1.1 Determinants of Technical Efficiency
The determinants of technical efficiency are presented in table 4.3. The coefficients of age
for male and female farmers were negative and significant at 10% and 1% level of probability
respectively. This means that any increase in age will lead to a decrease in efficiency. This result
agrees with Okoye et al (2007) and Okoye et al (2008) who found out that ageing farmers would
be less energetic to work. The coefficients of households’ size for male farmers were positive and
significant at 10% level of probability. This shows that male headed household with large family
size are likely to be more technically efficient than their counterparts with smaller family size.
Large household size is a source of labour for most farm operations, as noted by Effiong and
Idiong (2005).
The coefficients of education for male and female farmers were positive and significant at
5% and 1% levels of probability. This implies that increase in education will lead to increase in
technical efficiency, ceteris paribus. Education might be regarded as a factor for increased
efficiency, this agrees with Kadurumba et al, (2010). The coefficients for farming experience
were positive and significant at 1% level of probability. This agrees with apriori expectations that
increase in years leads to increase in technical efficiency. This also agrees with Okoye et al,
(2007); and Onyenweaku and Nwaru, (2005) who found out that farming experience had a direct
relationship with technical efficiency. The coefficients of farm size were negative and significant
at 5% and 1% level of probability for the male and female farmers respectively. This indicates
that increases in farm size will lead to decrease in technical efficiency and agrees with Hazarika
and Subramanian (1990) who found out that if farm size is small, farmers are able to combine
their resources efficiently. However, whether this relationship will follow in all cases, and at what
farm size threshold reversals might occur is not known.
4.3.2. Allocative Efficiency.
Regression result of allocative efficiency for male and female cocoyam farmers Linear,
exponential, semi-log and Cobb Douglas functional forms were fitted to the data and the results of
analysis are presented in tables 4.4 and 4.5 for male and female farmers respectively. The Cobb -
douglas functional form was chosen as the lead equation for the two estimates based on the
number of significant variables and extent of realization of apriori expectations for the farmers.
The R2 values for male and female farmers were 0.9910 and 0.8546 respectively. This implies
99.10% and 85.46% variability in cocoyam output for the male and female farmers respectively
were explained by the independent variables. The t values were also highly significant at 1% level
of probability indicating goodness of fit of the regression line. The coefficients for farm size were
significant at 10% and 5% levels of probability for the male and female farmers respectively. This
is in agreement with apriori expectation. The coefficients for fertilizer were positive and
significant at 10% and 5% levels of probability for the male and female farmers respectively. This
implies that any increase in fertilizer application will lead to a corresponding increase in output.
This also expected. The coefficients for cocoyam setts were also positive and significant at 1%
level of probability and imply that any increase in planting material will increase output. The
coefficients for depreciation in capital items were positive and significant at 10% and 5% for the
male and female farmers respectively.
This implies that any increase in capital items will lead to a corresponding increase in
cocoyam output. The coefficients for labour of male and female farmers were positive and
significant at 10% level of probability and indicate that any increase in labour will lead to a
corresponding increase in output. The coefficients of labour for female farmers were positive but
not significant.
Table 4.4 Results of Multiple Regression Analysis of Male Cocoyam Farmers
Factors Linear Exponential Cobb Douglas+ Semi Log
______________________________________________________________________________________
Constant - 98633 9.30459 -7.40110 -420937
(-13.92)*** (151.39) (-14.53)*** (-4.02)***
Fertilizer 132.2014 -0.00135 0.05573 12483
(2.14)* (-2.52)* (2.43)* (2.21)*
Capital -11.6797 0.00008484 0.11061 32496
(-3.8)** (2.66)* (3.26)** (4.07)*
Labour -0.3152 0.00000379 0.04291 -6739.40389
(-1.34) (1.86)* (2.59)** (-0.76)
Farm Size -21.6231 0.00015312 0.18397 34.925
(-2.19)* (1.79)* (1.93)* (1.45)
Cocoyam Setts 5512.79263 0.04024 0.03924 271262
(32.32)*** (27.19)*** (26.02)** (14.82)***
______________________________________________________________________________________
R2 0.9832 0.9858 0.9910 0.9534
F 339.46*** 403.92*** 525.69*** 98.17***
Source: field survey 2011
+ lead equation.
*,**,*** is significant at 10%,5%,1% level of probability
Figures in parenthesis are t - values
Table 4.5 Results of Multiple Regression Analysis of Female Cocoyam farmers.
________________________________________________________________________
Factors Linear Exponential Cobb Douglas+ Semi Log
______________________________________________________________________________________
Constant -163421 9.70209 6.83014 278821
(-13.72)*** (129.73) (8.26)*** (2.09)***
Fertilizer 134.10153 -0.00055453 0.01008 -237.57436
(1.23) (-0.81) (2.78)** (-0.04)
Capital -2.14937 0.00001202 0.15264 -27120
(-4.28)*** (3.81)*** (3.42)* (3.77)***
Labour 0.685584 0.00000275 0.10310 -11503
(2.89)** (2.09)* (1.32) (-0.91)
Farm Size 2.04558 -0.00008162 0.90419 -18720
(0.12) (-.074) (2.61)** (-0.80)
Cocoyam Setts 6670.12124 0.03143 0.02869 7013.29290
(22.65)*** (17.00)*** (14.60)*** (22.13)***
______________________________________________________________________________________
R2 0.9619 0.8533 0.8546 0.8613
F 318.17 257.21 222.93*** 263.64
Source: field survey 2011
+ lead equation.
*,**,*** is significant at 10%,5%,1% level of probability
Figures in parenthesis are t - values
4.3.2.1 Estimation of Allocative Efficiency of Male and Female Cocoyam farmers
The results in table 4.6 and 4.7 show the estimated allocative efficiencies of the male and
female cocoyam farmers in Anambra State. The decision rule is that if r = 1, it implies that
resources are efficiently utilized i.e. MVP = MFC = 1, r > 1, implies that resources are under
utilized r < 1, implies that resources are over utilized. The ratios of marginal value product (MVP)
to marginal fixed cost (MFC) of male farmers shows that fertilizer, capital, labour, farm size and
cocoyam setts inputs had values of 3.08, 0.21, 0.00043, 0.0219 and 0.0039 respectively. This
result implies that none of the inputs were efficiently utilized by the male farmers. The results
further indicates that male farmers over utilized capital, labour, farm size, and cocoyam setts
while they underutilized fertilizer. The results also show the allocative efficiency values of
0.0094, 0.0107, 0.0000554, 0.1608 and 0.0001125 for fertilizer, capital, labour, farm size and
cocoyam setts for female farmers. Indicating that all the inputs were over utilized. This result
suggests that there exists the possibility of increasing output under existing level of technology
through the use of lower levels of all inputs by male and female farmers except fertilizer for male
farmers. There is also need to use higher level of fertilizer for the male farmers.
Table 4.6 Estimation of Allocative Efficiency for Male Cocoyam Farmers
Item Product Elasticity Sample Mean MVP MFC Allocative Efficiency
Indices
______________________________________________________________________________________
Fertilizer 0.05573 0.9884 138.15 44.74 3.08 (under utilization)
Capital 0.11061 1,263.70 0.21 1.00 0.21 (over utilization)
Labour 0.04291 240.14 0.43 1,000 0.00043(over utilization)
Farm Size 0.18397 0.4850 929.40 1,018.50 0.0129 (over utilization)
Cocoyam Setts 0.03924 490.04 0.1062 49.00 0.0039 (over utilization)
____________________________________________________________________________________________
Source: field survey 2011
Table 4.7 Estimation of Allocative Efficiency for Female Cocoyam Farmers
Item Product Elasticity Sample Mean MVP MFC Allocative Efficiency
Indices
______________________________________________________________________________________
Fertilizer 0.01008 2.5418 0.4362 46.65 0.0094 (over utilization)
Capital 0.15264 1,562.45 0.0107 1.00 0.0107 (over utilization)
Labour 0.10310 255.51 0.0443 800.00 0.0000554 (over utilization)
Farm Size 0.90419 0.5427 183.27 1139.73 0.1608 (over utilization)
Coco yam Setts 0.02869 503.82 0.0063 55.98 0.0001125 (over utilization)
Source: field survey 2011
4.3.2 comparison of technical efficiency of male and female cocoyam farmers
Looking at the efficiency factors in table 4.3, the coefficients for age for male and female
farmers were negative at 10% and 1% levels of probability. This means that any increase in age
will lead to a decrease in efficiency. The coefficients for farming experience were positive and
significant at 1% level of probability. This implies that any increase in farming experience is
expected to lead to increase in technical efficiency.
4.4 COMPARISON OF RETURNS TO SCALE OF THE MALE AND FEMALE FARMERS
The results in the table 4.8 show the comparison of returns to scale of the male and female
cocoyam farmers in the study area. The elasticity of production which is the measure of the
percentage change in output to percentage with respect to individual input resources used in
cocoyam production and the sum of elasticity (return to scale) which is the response of output to a
proportionate change in the inputs were estimated following Gujarati(2004) ,if this sum is 1,there
is constant return to scale, if the sum is less than 1,there are decreasing returns to scale and if the
sum is greater than 1 there are increasing returns to scale. With the double log function as the lead
equation, the regression coefficients are now automatically the elasticites found in table 4.8
.returns to scale was calculated as the sum of the individual production inputs elasticities. The
sum elasticities resulted to a value of 0.4326 and 1.1987 for the male and female farmers
respectively. This implies decreasing returns for the male farmers and increasing returns for
female farmers. Women are operating at increasing returns to scale (ΣEP>1) which implies that
they are operating in region of the total product curve which is irrational. The implication is that
they can improve on their productivity by employing more resources. This result is consistent
with the report from Nwaru and Ekumankama (2002) who reported increasing returns to scale for
women arable crop farmers but deviates from the decreasing returns to scale they reported for the
men. Also the results of increasing returns to scale are in line with Ajibefun and Aderinola
(2004). Furthermore men are producing below capacity and there is need to increase the inputs
used in production. This could be as a result of decreasing returns caused by inefficiency in inputs
utilized.
Table 4.8: Elasticities of production for Male and Female Cocoyam Farmers in the Study
Area.
________________________________________________________________________
Production Factors Male Female
________________________________________________________________________
Input Elasticity Elasticity
Fertilizer 0.05573 0.01008
Capital 0.11061 0.15264
Labour 0.04291 0.10310
Farm Size 0.18397 0.90419
Cocoyam Setts 0.03924 0.02869
_______________________________________________________________________
Σ EP 0.43246 1.1987
_______________________________________________________________________
Source: field survey 2011
4.5 COST AND RETURN ANALYSIS OF COCOYAM PRODUCTION BY GENDER.
The result in table 4.9 shows the cost and return analysis for male and female cocoyam
farmers respectively. The total cost for male and female farmers was N73, 833.17 and N
75,892.59 respectively. About N 78,509.60 and N 106,007.99 were the Gross Margin realized
from cocoyam production by the male and female farmers respectively. The net profit from the
enterprise was N 62,592.87 and N 88,378.12 for the male and female farmers respectively. For
every N 1 spent the male farmers realized N 1.85 while N 2.16 was realized by the females. This
shows that female cocoyam farmers had a higher profit margin than male cocoyam farmers which
might be as result of experience in cocoyam production; this is in line with Ewuziem et al (2010)
that farmers with longer years of farming experience tend to combine their resources better in an
optimal manner. In other words cocoyam production is a profitable enterprise in Anambra State.
Table 4.9 Cost and Return of Male and Female Cocoyam Farmers/ha
Item Male (=N=) Female (=N=)
Revenue 136,426.04 164,270.71
Variable Costs
Planting Materials 28,011.96 26,873.59
Fertilizer 4,800.20 4,736.92
Wage Bill 25,104.57 26,652.17
TVC 57,916.73 58,262.72
Fixed Costs
Depreciated Cost of Capital Inputs 13,263.70 14,691.56
20% Contingences of Fixed Cost 2,652.73 2,938.31
TFC 15,916.44 17,629.87
TC 73,833.17 75,892.59
GM 78,509.60 106,007.99
Net Profit 62,599.87 88,378.12
BCR/RNI 1.85 2.16
_________________________________________________________________________
Source: field survey, 2011
4.6 DISTRIBUTION OF MALE AND FEMALE RESPONDENTS ACCORDING TO
CONSTRAINT IN
Cocoyam Production
The Table 4.10 presents the constraints/problems facing male and female Cocoyam
farmers in Anambra State. From the table, a high percentage of the farmers, (90.00% of the male
and 90.91% of the female) identified pests and diseases as their major problem. Other problems
confronting the farmers as identified by them include poor feeder roads, lack of credit, poor
storage facilities, high cost of planting materials, lack of extension contact. The viral disease in
cocoyam production has led to a reduction in output of cocoyam. Majority (70%) of the female
respondents experienced rot and decay of cocoyam during storage and 98% of the male
respondents encountered this problem also. This agrees with findings of Nwauzor, (2001) that rot
had earlier been identified as one of the problems which militate against maximum production is
cocoyam. Attempts to solve these problems have been at the core of most agricultural, rural and
extension programmes in Nigeria, Also Breeding programmes may help to eliminate or minimize
some of these problems of rot and disease of cocoyam in storage. Storage problem received
(60%) for the male farmers and (61.81% )for the female farmers. Njoku (2008) reported that any
strategy developed for achieving sustainable crop production by Cocoyam farmers in the 21st
century must tackle the problem posed by the following inputs supply, pest and diseases, storage
facilities, production facilities and access to credits.
Table 4.10: Distribution of male and female cocoyam farmers according to problems
encountered.
Male Female
____________________________________________________________________________ Problems Frequency Percentage Frequency Percentage
Encountered
___________________________________________________________________________________________
Lack of credit 20 40 95 86.36
Root and decay during
Storage 35 70 77 70.00
High cost of planting
Materials 32 64 68 61.82
Poor Infrastructural
Facilities 48 96 79 71.82
Low soil fertility 10 20 50 45.45
Poor feeder and road 32 64 70 63.64
Poor storage facilities 30 60 68 61.81
Pest and diseases 45 90 100 91.91
Limited lands 22 44 58 52.73
High cost of labour 18 36 50 45.45
Poor Knowledge of
Technology 28 56 35 31.82
Lack of extension
Contact 19 38 29 26.36
Lack of fertilizer 32 64 30 27.27
_________________________________________________________________________________________________
Source: Field survey 2011, Multiple responses
CHAPTER FIVE
5.0 SUMMARY, RECOMMENDATION AND RECOMMENDATIONS
5.1 Summary
The study was designed to investigate the gender and resource use efficiency in cocoyam
production in Anambra State. Socio-economic characteristics of the farmers were determined as
well as the production problems affecting them. The study presents the results of analysis of data
collected on 160 cocoyam farmers ( male and female ) across the two Agricultural zones. A multi-
stage randomized sampling technique was used to select the zones, blocks, circles and contact
farmers. Descriptive statistical tools such as percentages, frequencies, means and were used in
analyzing farmer’s socio-economic characteristics and production problems. The result showed
that women constitute a greater (68.75%) percentage of cocoyam production in the state. The
maximum likelihood Estimation (MLE) technique was used in estimating the technical efficiency
and determinants of efficiency of male and female farmers using the Cobb-Douglas stochastic
function as the lead model. The result of the technical efficiency estimation showed that the
coefficients of both farmers for the production variables used were all positive. Cocoyam setts,
labour, and fertilizer use were significant while capital inputs were not significant for female
cocoyam farmers. The result indicates that socio-economic conditions influenced technical
efficiency of both farmers. The coefficients of determinants of efficiency used were all positive
except farm size that were negative and significant for both male and female cocoyam farmers
only while age, level of education, extension contact and knowledge index were all positive and
significant for male farmers while other variables were not significant.
Test of Allocative Efficiency revealed that none of the defined farmer groups achieved
absolute allocative efficiency. Male farmers under-utilized fertilizer and over-utilized other inputs
used in production while female farmers over-utilized all the input. This result suggests that there
exists the possibility of increasing output under existing level of technology through the use of
lower levels of all inputs by male and female farmers except fertilizer for males. There is also
need to use higher levels of fertilizer for the male farmers. Finally, the survey revealed that most
of the farmers (male and female) encountered problems of root rot diseases at 90% and 90.91%
respectively.
5.2 Conclusion
It could be concluded from this study that resources were poorly allocated by male and
female farmers. Farmers should be amply and properly empowered, this will enable them to
exhibit higher level of entrepreneurial capabilities, policies and programmes that could help to
increase their efficiency should be put in place. The study revealed that cocoyam farmers in
Anambra State who were predominantly women were not fully technically and allocatively
efficient in their use of resources. Farmers’ level of technical efficiency was higher than allocative
efficiencies.
All factors related to technical and allocative efficiencies call for policies aimed at
incorporation of all the significant variables, especially those that will encourage farmers of their
tendency to allocate the bulk of their landholdings to cocoyam production and those that limit
women’s access to production inputs. The promotion of cocoyam cultivation as well as
encouraging of new entrants would also be a key component in government policy strategy of
cocoyam growth. This would raise the level of technical and allocative efficiencies and hence the
level of productivity.
5.3 Policy Implications and Recommendations
Given the input requirements for cocoyam production, improving farmers’ efficiency both
technically and allocatively would be a necessary step towards allocating more widespread
resources in cocoyam production.
(1) The study showed that rising age would lead to decline in the efficiency of farmers,
Government policy should focus on ways of attracting and encouraging the youths who are agile
and strong. This group of people would be able to put in a lot of efforts at raising the current level
of efficiency, given conducive policy environment.
(2) The study revealed that increase in farm size would lead to a decline in efficiency. The finding
suggests that government policy should concentrate on how to encourage new entrants to
cocoyam production and not necessarily increased farm size. The government could encourage
that trend by removing policies and distortions that favour large farms over small farms.
(3) The high percentage of the aged, most of who were illiterates but had to rely on their many
years of experience affected the productivity of cocoyam in the study area. Government policy on
encouraging the youths to take to cocoyam production should have a multifaceted approach and
an adequate program on education and extension services.
(4) Government should enact policies that would encourage experienced farmers to remain in
farming as well as decreasing further the current fertilizer subsidy level while the fertilizer
distribution network should be completely over hauled
(5) Policies to reduce inflation and enhance subsidies in the form of cheap credit should be
strengthened. This will assists farmers in acquiring the resource inputs as at when due since most
operations in the farm are time bound
(6) Since it has been confirmed that women dominate the production process, women’s access to
production inputs should be increased.
REFERENCES
Adeniyi, J.P. (1998). Farm size and resource use efficiency in small scale agricultural production:
The case of rice farmers in Kwara State of Nigeria”. The Nigerian Agricultural Journal.
23(2):6-7
Agboola, S.D. (1987). Cocoyam Storage and its full potential for food sufficient and Future
Economic Recovery of Nigeria. Proceedings of 1st National Workshop on Cocoyam held
at NRCRI Umudike Nigeria August 5 -21:58.
Agom, D.I. and C. Idiong (2002). “Effects of credit use on gross margins in food crop enterprises
of small scale farmers in Cross River State, Nigeria”. International Journal of Social
Sciences and Public Policy:12 (1) 197- 208.
Ajibefin, I.A and A.O. Abdukadri (2004). Impact of Size of Farm Operation in Resource Use
Efficiency in Small Scale-Farming Evidence from South Western Nigeria. Journal of
Food and environment. 2(1): 359 – 364.
Ajibefun, I.A. and E.A. Aderinola (2004) Determinants of Technical Efficiency and policy
implication Traditional Agricultural Production Traditional Agricultural production.
Empirical Study of Nigeria food crop fermess. Final Report presentation at Binnual
Research workshop of Africa Economic Research Consertum Nairobi Kenya. May 24th
–
29th
.
Akanji, B. (1999). “Differentials and Patterns of Gender Responsibility in Tradable Crop
Agriculture in Nigeria. Paper presented at a Conference on Women Farmers” Enhancing
Rights and Productivity by Centre for Development Research (ZEF), Bonn, Germany,
Tuffs University, Boston, USA and University of Hoheinheim, Stuffgast, Germany.
August 26 – 27 pp 2 – 6.
Alibi, R.A. and M.A. Aruna (2006). “Technical efficiency of family poultry production in Nigeria
– Delta Nigeria”. Journal of Central European Agriculture. . 6(4): 531 – 538.
Amaechina E.C. (2002). “Gender Relations Being an unpublished paper presented at Gender and
Good Governance Training Workshop for Communities Leaders from 2 Communities in
Abia State (World Wide Network/Erbest Stifting Foundation) June, 2002”.
Amaza P.S. and D.C. Maurice (2005) Identification of Factors that influence Technical efficiency
in Rice based production system in Nigeria paper presented at workshop on policies and
strategies for promoting rice production and food security in sub-saharan Africa 7-9-
November 2005, Cotonou,Benin Republic.
Amaza, T.O. (2002).Technical Efficiency and farmers Attitude toward Technological innovation.
ANSEP Survey Report (2000) Anambra State ADP (ASADEP) (2000). Hints on Fadama
programme, Bulletin No. 001/October Awka, Nigeria. ASADEP 1 – 6.
Anyaegbunam, H.N., B.C. Okoye, G.N. Asumugha, and T. Madu (2009). A translog stochastic
frontier analysis of plot size and cost inefficiency among small holder cassava farmers in
South East Agro-Ecological Zone of Nigeria. The Nigerian Agricultural Journal 40(1):
23 – 27.
Arene, C. J. (2003). Introduction to Agricultural Marketing Analysis and Policy. Fullaudu
publishing company, Enugu, PP:59-62.
Arene, C.J. (2008) “Agricultural economics A functional approach” prize publishers limited,
Nuskka, Nigeria.
Arene, O. B and Ene L.S.O. (1987). Advances in cocoyam research held at the National Root
Crops Research Institute Umudike. Proceedings of 1st National Workshop on Cocoyam
held at NRCRI Umudike Nigeria August 5 – 21 P.58.
Arigner D, E.A. K lovel and P. Schmidt, (1977). Formulation and Estimation of stochastic
frontier production function models J. Econometrics 6: 21-37.
Asumugha, G.N. and Mbanasor E.N.A. (2002). “Cost Effectiveness of Farm Gate Cocoyam”
Processing in Agriculture; A Basic Poverty Eradication and Conflict Resolution
Strategy.Federal University of Technology, Owerri (FUTO) Imo State Nigeria, pp. 94 –
97.
Audu, S.I. (2009). Gender Roles in Agricultural Production in the Middle Belt Region of Nigeria.
American Eurasian Journal of Sustainable Agriculture. 3(4): 626 – 629.
Awudu, A and W. Hittima (2000), Structural Adjustment And Economic Efficiency of Rice
Farmers in Northern Ghana. Economic Development and Cultural Change pp. 505 – 519.
Banabana – Wabbi, J. (2002). Assessing Factors affecting Adoption of Agricultural Technologies.
The case of integrated Pest Management (1pm) in Kumi District Eastern Uganda.
Unpublished M.Sc Thesis Dept. of Agricultural and Applied Economics, Virginia
Polytechnic Institute and State University U.S.A.
Barau, A.D.; T.K. Atala, and C.I. Agbo (1999). Factors Affecting Efficiency Of Resource Use
Under Large Scale Irrigation Farming. A case Study of the Dadin Kowa Irrigation Project.
Bauchi, Nigerian Journal of Rural Economy and Society. 1( 5).
Barney, J. (1991). “Firm Resources and sustained competitive advantage”, Journal of
Management, 17: 99 – 120.
Battese, G. E. and T. J. Coelli, (1995). “A model for Technical inefficiency Effect in Stochastic
Frontier Production for Panel Data; Empirical Economics 20: 325 -345.
Begg, P. (1997) Economics 5th
ed. London, MacGraw Hill (lek) Ltd.
Brock, G. M. Grdzninova, Z. Lerman and V. Uzun (2006). Technical efficiency in Russian
Agriculture. A discussion paper No 113.05 http//department.agrihuji.accil/economics/
Central Bank of Nigeria, CBN (2003): Central Bank of Nigeria – Annual Reports and statement
of Accounts for the year ended 31st December, 2007.
Chidebelu, S.A.N.D. (1990), Hired labour on small holder farmers in South Eastern Nigeria.
African rural social science series. Windrock International Institute For Agricultural
Development Research Report No. 12.
Chinaka, E.C. and C. O. Emereole (2006), “Women in yam production in Imo State, Nigeria”
Proceedings of the 40th
Conference of the Agricultural Society of Nigeria pp 614 – 617.
Chukwu, G.O., K.I. Nwosu, E.N.A. Mbanaso, O. Onwubiko, B.C. Okoye, T. U. Madu, Ogbonne
and S.U. Nwoko (2009). Development of Gocken Multiplication technology for Cocoyam
http://mpra.ab.unimuen.
Coeli, I.J. (1996) A guide to frontier version 4:1. A computer programme for stochastic frontier
production and cost function Estimation. Department of Economics, University of New
England, Armidale, Austrialia.
Coelli L.J. (1994): A guide to Frontier L.I.A. computer program for stoctrastic frontier production
and cost function Estimation. Department if Econometrics, University of New England,
Armidale.
Department of Agricultural and Co-operation DAC (2004). Concept Note on Gender Resource
Centre Ministry of Agriculture, Indian. P 80.
Desai, R.M. and J.W. Mellor (1993). “Institutional Credit for Green Revolution Areas Under
Semi-Arid Tropics in Indian. Indian Journal of Agricultural Economics. 43(1): 1 – 8.
Dimelu, M.U., A.C. Okoye, B.C. Okoye, A E. Agwu, O.C. Aniedu and A.O. Akinpelu (2009).
“Determinants of Gender Efficiency of Small-Holder Cocoyam Farmers in Nsukka
Agricultural zone of Enugu State Nigeria”. Scientific Research and Essay. 4(1): 28 – 32.
Dixon, R.B. (1983) “Women in Agriculture: Counting the Labour Force in Developing
Countries”. Population Development Review (8) (3) pp. 539 – 567.
Doss, C.R. (2002) “Men’s Crops” Women’s Crop. The Gender Patterns of ‘Cropping in Ghana’.
Journal of World Development 30(11): 1987 – 2000. Great Britain Elsevier Science Ltd.
Durno, J. and R. Stuart (2005) “Gender issues in sustainable agriculture in Overholt”, C. et al
(eds) Gender roles in Development projects. New Delhi: Fox publication.
Duru, C.C. and N.U. Uma (2002) Post harvest spoilage of cormels of Xanthosoma, Sagiltifolia (1)
schoott. Bioscience Research Communications 14: 277-283
Effiong, E. O and J.C. Nwaru (2002). “Production function analysis of selected food crops in
Akwa Ibom State Nigeria. Journal of Applied Chemistry and Agricultural Research 8: 91
– 100.
Effiong, E.O. (2005). Efficiency of production in selected livestock enterprises in Akwa Ibom
State, Nigeria. Unpublished Ph.D Dissertation. Department of Agricultural Economics,
Michael Okpara University of Agriculture, Umudike.
Efifu, M. W. (1999), “Gender Issues associated with agricultural production and extension” in
Yomi O. (ed). Gender, sustainable development and the urban poor in Nigeria; A book of
readings. Hiss publishing Ltd Port Harcourt, Nigeria.
Egwu, E. W, P. O. Nto, K. U. Kalu and J. A. Mbanaso (2010). Technical Efficiency of
commercial vegetable production in Akwa Ibom State, Nigerian production in Akwa Ibom
State, Nigeria. The Nigeria Agricultural Journal 41(2) : 157 – 161
Ejiofor, M.A.N. (1987). Fermentation Alcohol: A process Strategy Toward Enhanced Productions
and Utilization of Cocoyam in Nigeria. Proceeding of 1st National Workshop on Cocoyam
held at NRCRI Umudike, Nigeria. August 5 – 21 p.196.
Ekumankama, I.O. and O.O. Ekumankama (1996). Harnessing the capabilities of rural women
towards achieving rural development in Nigeria. Proceedings of the 9th
Annual
Conference of Nigerian Rural Sociological Assoc. (NRSA) held at Usman Dan Fodio
University, Sokoto, March 5th
– 8th
1996.
Ekwe, K.C., Mbanaso, E.N.A.; K.I. Nwosu, I. Nwachukwu and C.C. Ekwe (1999). Examining the
under exploited values of cocoyam for enhanced household food security, economy and
nutrition in Nigeria. N.R.C.R. I. Umudike, Annual Report 1999.
Eleje, I. (1987). Cocoyam. A Major National Carbohydrate Stale for the Future in Nigeria.
Proceeding of 1st National Workshop on Cocoyam held at NRCRI Umudike. Nigeria
August 5 – 21 p. 11.
Enya and Oniah (2007) Palm Oil Marketing Efficiency in Ikom Local Government Area. Cross
River. Global Journal of Agric Science (6): 183 – 186.
Ewuziem J.E., V.O. Onyenobi, A.E. Ironkwe (2010). Technical Efficiency of pig Farms in Imo
State. Nigeria. A Tran slog stochastic Frontier Function. Approach. Nigerian
Agricultural Journal vol 41: 1: 137-147.
Eze, C. O. (2008), Effects of Environmental Constraints on Technical Efficiency of Urban and
Rural Pig Farmers in Enugu State. An Unpublished M.Sc. Thesis Department of
Agricultural economics University of Nigeria , Nsukka.
Ezedinma, F.O. (1987). Prospect of Cocoyam in the Food System and Economy of Nigeria.
Proceedings of 1st National Workshop On Cocoyam held at NRCRI Umudike. Nigeria,
August 5 – 21. p28
FAO (1988) Root and Tuber crops. Plantain and Bananas in developing countries challenges and
opportunities. Serial paper No. 87. pp 11 – 13
FAO (2004), Food Balance sheet 1961 – 2002. Nigeria. http://www.faostat.org.
FAO (2005a) Year book, Rome, Italy.
FAO (2005a). FAOSTAT. Database Available on at <http:/apps.fao.org/default.htm>
FAO (2005b). Food and agricultural organizations production year book, Rome Italy.
FAO (2006a) “Food and Agricultural organization statistics and database results, Rome: Italy.
FAO (2006b), Food and Agricultural Organizations of United Nations. Production Year Book for
2007, Rome, Italy
FAO Statistics (2007b) Food and Agricultural organization Database result.
FAO (2007). FAOSTAT. Statistic Division of the food and agricultural organization.
http://faostat.fao.org/site/562/desktopdefault.aspx page 10 - 567 accessed July 03, 2008
Data Base result.
FAO (2008). FAOSTAT. Food and Agriculture Organization, Database Results.
FAO (2010). FAOSTAT. Food and Agricultural Organization. Agricultural Statistics, Rome,
ItalyFarrells, M. J. (1957). The Measurement of Production Efficiency: Journal of the
Royal statistical society-series, General 120 (3): 253 – 290.
Field, B.C. (1997), Environmental Economics New York: McGraw Hills.
Frishmuth C. (1997) Gender is not a sensitivity issue: Institutionalizing a Gender Oriented
participatory Approach in Savionga Zambia: Gate Keeper Series Number 72 International
Institute for Environment and Development Sustainable Agriculture and Rural
Livelihoods programme.
Hardwick, P. (1994). Introduction to Modern to economics. England: Longman Group Ltd. Pp.
108 - 121.
Hargroves, K and H. M. Smith (2005). The Natural advantage of Nations. Business opportunities:
Innovation and Governance in the 21st Century. Earthscan. London.
Haruna, V., S.A.Sanni, D. Yusuf and O.S. Balogun (2008). Input – Output Relationship and
Resource use Efficiency in Cassava Production in Jama L.G.A. of Kaduna State:
Proceedings of the 10th
Annual Conference of Nigeria Association of Agricultural
Economics 7 – 10th
October held at University of Abuja.
Hazarika,C and Subramanian,S.R (1990) Estimation of Technical Efficiency in the Stochastic
Frontier Production Function Model. An Application to the Tea Industry in Assan.
Henderson, M. and R.E. Quandnt (2003). Microeconomics Theory: A Mathematical Approach.
New Delhi: Tata McGraw Hill Publishing Company Ltd. Pp. 105 – 106.
Idiong, I C., (2005). Evaluation of Technical Allocative and Economic Efficiences in Rice
production system in Cross River State, Nigeria. An Unpublished Ph.D Thesis, University
of Ibadan, Nigeria.
Igbokwe, N.Y. (2004) “Efficiency of Small Holder Cassava Poultry in Abia State, Nigeria.
Unpublished M.Sc. Thesis, Department of Agric. Econs Michael Okpara University of
Agriculture. Umudike, Nigeria.
Ikwelle, M.C., T. O. Ezulike, and O.N. Eke-Okoro (2003), Contribution of root and tubers crops
to the Nigerian economy. Proceeding of 8th
Triennial Symposium of the International
Society for Tropical Root Crops – African Branch (ISTRC –AB) held at the international
institute of tropical agriculture, Ibadan: November 12 – 16, 2001 pp. 13 -18.
Immink, M.D.C. and J.A. Alarcon (1993) “Household Income, Food Availability, and
commercial Crop production by small holders farmers in the western highlands of
Guatemala:, Economic Development and cultural changes, 41, pp 319 -342.
International Institute of Tropical Agriculture (IITA) (1992). Cassava in Tropical Africa. A
reference Manual IITA, Nigeria.
Ironkwe, A.G., R. Asiedu and E.C. Chinaka, (2007) “Women farmers Participation in Yam
Minisett Adoption in South Eastern Nigeria. Global Approaches to Extension Practice”. A
Journal of Agricultural Extension 3(2): 62 – 69.
Kadurumba, C., J.A. Mbanasor and C.I. Ezeh (2010) “Technical efficiency of Traditional Oil
Palm Marketing” in Mbaise, Imo State, Journal of Farm Management Association of
Nigeria. Vol.(1): 17 – 21.
Kaldjan P. (2001). The small holder in Turkish Agriculture. Obstacle or Opportunity? In Rural
Development in Eurasia and the middle East land Reform, Demograptic charge, and
Environmental constraints, K. Engelmann and V. Pavlakovic (eds) Seattle University of
Washington.
Kaliarja, K. P (1990). Measuring Economic Efficiency. Journal of Applied Economics vol. (5)1:
75-85.
Kirkley J.E.D. Squires and I.E. Strand (1995) Assessing Technical Efficiency in Commercial
Fisheries. The mid atlantic sea-scallo fishery A.M.J. Agric Econs 20: 31-34.
Krause, M.A., R.R. Oeuson, T.G. Baker, P.V. Preckel, J. Lowenberg – De Boer, K.C. Reddy and
K. Maliki (1990). “Risk-Sharing Versus Low-Cost Credit Systems For International
Development” American Journal of Economics, 72: 911 – 922.
Mammam, M. (1994). “Population and Women in Food Production,” in Adetunbem, J. O. (ed).
Food Crisis in Nigeria. Abstract of Papers presented at the 7th
Annual Conference of
Nigerian Geographical association held at Ondo State College of Education, Ikere Ekiti 5
– 8 April, pp. 109 – 113.
Mejeha, R.O. and A. Obunadike (1988). “The Impact of Credits on Adopting Innovations on
Fertilizer Use, Yam Minisett and Cassava in Anambra State of Nigeria”. Nigerian Journal
of Agricultural Teacher Education 7 (182): 92 – 100.
Meeusen N and Van den Broeck J Efficiency Estimation from Cobb Douglas Production
Function with Composite Error. International Economic Review,vol 18No22 pp:123-124
Miller, S. and A. Ross (2003) “An exploratory Analysis of Resources Across Organizational
Units, Understanding the Resource Based View”. International Journal of Operations and
Production Management 23(9): 1062 – 1083.
Mkpado, M and C.J. Arene (2003) “Effects of Cropping System and Selected Socio-Economic
Factors on the Sustainability of Arable Crop Production”. The Case of Cassava in Okigwe,
Imo State of Nigeria. Journal of Agro-Technology and Extension. 3(1) and 2: 14 – 17.
Musa, M.B (1987) Organisation as the key to empowering women to participate in rural
development. A paper presented at the workshop on women in Rural development
sponsored by DFRRI held at Abuja 14-16th
September..
National Bureau of Statistics (2006): Annual Abstract of Statistics Federal Republic of Nigeria,
Abuja p.49.
National population Commission(N.P.C)(2006),Abuja, Nigeria.
Ndukwu, P.C., J.C. Nwaru, B.C. Okoye (2010). Gender and Relative Economic Efficiency in
Sweet Potatoe Farmers of Imo State, Nigeria. A stochastic Cost Frontier Approach. The
Nigerian Agricultural Journal. 41:1:65-70
Njoku, J.E. (1988) “Cost and Return of Rice Production under Alternative Production systems. A
case study of Ohazara Area of Imo State, Nigeria” Proceedings of the National Farming
System Research Network Workshop held in Jos, Plateau State Nigeria PP. 192-201.
Njoku, P.C. (2008): Nigeria Agriculture and the Challenges of the 29th
century Agro Science
Journal of Tropical Agriculture, Food, Environment and Extension Vol.II; 42 – 53.
Nkematu, J.A. (2000), Anambra State Agricultural Development Project Extension Services
Report for 1999. In Proceeding of the 14th
Annual Farming Systems Research and
Extension Workshop in South Eastern Nigeria, 9 – 12 November pp. 100 – 105.
NRCRI (1999) Annual Report
NRCRI (2009) MPRA. Munich Personal RePEC Archives
Nwagbo, E.C. and S.C. Onwuchekwa (1988) “Economics of rice Production by Farmers” in
Abakiliki Area of Anambra State. Proceedings of the National Farming System Research
Network Research Workshop Held in Jos, Plateau State Nigeria. Pp 174 – 183.
Nwakalobo, A.B.S. (2000). Resource Production and Allocative Efficiency in Small Holder
Coffee Farmers in Rugwe District, Tanzania, Sokoine University, Morogon, Tanzania.
Retrieved February, 2006 from http://www.five.org/iauf/ssap/.
Nwaru, J. C. and O.O. Ekumankama (2002)Economics of Resources use by women Arable Crop
Farms in Abia State Research Report submitted to the Senate Grant Committee, Michael
Okpara University of Agriculture, Umudike, December pp40
Nwaru, J.C. (1993) “Relative Production Efficiency of Cooperative and Non-Cooperative Farms”
in Imo State, Nigeria. M.Sc. Thesis, Federal University of Technology, Owerri.
Nwaru, J.C. (2001). “Stimulating Entrepreneurship in Nigerian Farm Through Sustainable
Agricultural Extension Service Delivery in Nigeria”. Prospects and questions Olowu, T.A.
(ed) Proceedings of the 7th
National Conference of Agricultural Extension Society of
Nigeria 19 – 22 August pp. 19 – 27.
Nwaru, J.C. (2002). “Measuring the Profit Maximization Input use in Rice Production System in
Abia State: the case of Ubibia Awalo Inland Valley, Journal of Applied Chemistry and
Agricultural Research 8 pp. 67 – 72.
Nwaru, J.C. (2003). “Gender and Relative production Efficiency in Food Crop Farming in Abia
State. Research Report Submitted to the Senate Grant Committee, Michael Okpara
University of Agriculture, Umudike, December pg. 40.
Nwaru, J.C. (2004). Rural Credit Markets and Resources Use in Arable Crop Production in Imo
State of Nigeria. Unpublished Ph.D Thesis Michael Okpara University of Agriculture,
Umudike.
Nwauzor E.C. (2001). Nematoto problems and Solution of Food and Tuber Crops in Nigeria. In
Akorota, M.O. and Ngave J.M. (eds) proceedings of the 7th
Technical symposium of the
International society for tropical root crops (ISTPC) Cotonou Oct 11-17, 1998, 545-552.
Nweke, A. N. (1994). Role of Women in Agricultural Production in Awka Education Zone of
Anambra State: Implications for Adult Education in Agriculture. Unpublished M.Sc
Dissertation, University of Nigeria, Nsukka Nigeria:.
Ogbosuka, G.E. and B.F. Salahu (2005). Household Food Security: The Case of Women
Pastoralists in Oyo State Nigeria. Nigerian Journal of Rural Sociology. 51(2): 8-16.
Ogundari, K and S.O. Ojo (2006). “An Examination of Technical, Economic and Allocative
Efficiency of Small Farms”. The Case Study of Cassava Farmers, in Osun State of
Nigeria. Journal of Central European of Agriculture 7(3): 423 -432.
Ogundari, K. (2006): Determinants of Profit Function Approach “Paper presented at the
International Association of Agricultural Economics Conference, Gold Coast, Australia,
August 12 – 18.
Ogundari, K., S.O. Ojo and A.I. Ajibefun, (2006). “Economics of Scale and Cost Efficiency in
Small Scale Maize Production. Empirical Evidence from Nigeria”. Journal of Social
Science 3(2): 131 – 136.
Ogundari, K.S.O., Ojo and A.I. Ajibefun, (2006): Economics of scale and cost Efficiency in small
scale Maize production Emprincal Evidence from Nigeria “Journal of Social Science Vol.
3(2): 131-136.
Ogundele, O. O. and V.O. Okoruwa (2006). “Technical Efficiency Differentials in Rice
Production Technologies in Nigeria” AERC Research paper 154. Africa Economic
Research Consortiumm, Nairabi, Kenya.
Ogunsumi, L.O. (2005) “Resource Use Pattern and Farmers Productivity” in South West Nigeria.
Journal of Central European Agriculture. (6)2: 195 – 202.
Ohajianya, D. O and C.E. Onyenweaku (2001). “Gender and Relative Efficiency in Rice
Production System” in Ebonyi State, Nigeria. A Profit Functional Analysis. Journal of
Sustainable Agriculture and Environment 3(2): 384 – 392.
Oji, K.O. (2002) Basic Principles for Agricultural Project and Policy Analysis Prince Publisher
Nsukka, Nigeria.
Ojiako, I.A., G.N. Asumugha, C. Ezedimma and N.E. Uzokwe (2007) Analysis of Production
Trends in the Major Root and Tuber Crops in Nigeria. 1961 – 2005. Res. in Crops (2): 371
– 380.
Ojo, S.O. (2003: Productivity and Technical Efficiency of Poultry Egg Production in Nigeria.
International Journal of Social Sciences 2(6):464
Okoruwa, V.O. and O.O. Ogundele, (2008). “Technical Efficiency Differentials in Rice
Production Technologies in Nigeria. Accessed from www.sae.d.x.ac.uk/2006eol-
r/p/papers/case/okoruwa.pdf.
Okoye, B.C (2006), Efficiency of Small-Holder Cocoyam Production in Anambra State, Nigeria.
An Unpublished M.Sc. thesis, Michael Okpara University of Agriculture, Umudike, Abia
State, Nigeria.
Okoye, B.C. and C.E. Onyenweaku (2006). “Economics of Small-Holder cocoyam production”
Proceedings of the 40th
Annual Conference of Agricultural Society of Nigeria pp. 82 – 86.
Okoye, B.C., C.E. Onyenweaku, G.N. Asumugha (2007). “Allocative Efficiency of Small Holder
Cocoyam Farmers” in Anambra State, Nigeria. Nigerian Agricultural Journal. 38: 70 –
81.
Okoye, B.C., C.E. Onyenweaku, O.O. Ukoha, G.N. Asumugha and O.C. Aniedu, O.C. (2008).
Determinants of Labour productivity on small holder cocoyam Farmers in Anambra State,
Nigeria. Academic Journals Scientific Research and Essay Vol 3(11): 559 – 561.
Okoye, B.C., E.C. Okorji. and G. N. Asumugha (2004), Outlook of Production Economics of
Paddy Rice Under Resource Constraints in Ebonyi State. Proceedings of the 38th
Annual
Conference of The Agricultural Society of Nigeria (ASN) - 17 – 21 October, 2004, Lafia
Nasarawa State, pp. 337 – 342.
Okoye, C.U. (1989), Migration and Agricultural Labour Supply in Aguata L.G.A. of Anambra
State. Unpublished M.Sc. Thesis, Department of Agricultural Economics. University of
Nigeria, Nsukka.
Okwuokwulu, P.A., J.E. Asiegbu and W.F. Nnado (2002) Effect of Row Intercropping of
Cocoyam Minisett on Tuber/Garri Yield and Productivity in South Eastern Nigeria.
Journal of Sustainable Agriculture and Environment 2: 214 – 225.
Olagoke, A. M. (1990) “Comparative Economics of Resource Use in Rice and Yam Based Crop
Production” in Uzo-Uwani L. G.A. of Enugu State. Unpublished Ph.D Thesis, Department
of Agricultural Economics, University of Nigeria, Nsukka.
Olaniyan, G.O., V.M. Manyyoung, V. M. and Oyewole B. (2001). The Dynamics of the Root and
Tuber cropping systems in the middle belt of Nigeria. In Akoroda, M. O. and Ngove, J.M.
(eds). Proceedings of the 7th
Triennial symposium of the International society for Tropical
Root Crops (ISTRC) pp 75-81.
Olayide, S. O. and E.O. Heady (1982): Introduction to Agricultural Production Economics. 1st
Edition University of Ibadan Press, Ibadan.
Olukosi, J. O. and P.O. Erhabor (1998) Introduction to Farm Management Economics Principles
and Application AGITTAB Pub. Ltd.
Omotesho, O. A., Muhammad – Lawal, A. and A. Falola (2008). Technical Efficiency of Youth-
in-Agriculture Programme in Ondo State, Nigeria”. Proceedings of 10th
Annual National
Conference NAAE 7th
– 10th
October, 2008.
Onojah, A.O. (2004). “Resource Use Efficiency in Fadama Maize Based Cropping System’s in
Kogi State, Nigeria. Department of Agricultural Economics. Unpublished M.Sc Thesis
University of Nigeria, Nsukka.
Onubuogu, G.C. (2006). Enterprise size, marketing Age and Relative Efficiency in Broiler
Production in Imo State, Nigeria. Unpublished Ph.D Thesis, Department of Agricultural
Economics University of Nigeria, Nsukka, pp. 15 – 22.
Onwueme I.C. and Sinha T.O. (1991 field crop production in Tropical Africa. P. 12.
Onyebinama, U.A.U. (2000). Economics and Production Management for Agriculture, Owerri
Alphabet Publishers.
Onyemauwa, C.S., M.A. C.A. Odii, Emenyonu and R.M. Okafor (2008) “Allocative Efficiency of
Food Crop Farmers by Gender” in Nwangele, Imo State, Nigeria. Proceedings of the 42nd
Annual Conference of Agricultural Society of Nigeria held at Ebonyi State University,
Abakaliki 19th
– 23rd
975 – 977.
Onyenweaku C.E. and J.C. Nwaru (2005). Application of Stochastic Frontier Production to the
measurement of Technical Efficiency in Food production in Imo State, Nigerian
Agricultural Journal vol. 36: 1-12.
Onyenweaku, C. E. and Ezeh, N. O. A. (1987). Trends in production, Area and Productivity of
Cocoyams in Nigeria 1960/61 – 1981/84: In Cocoyams in Nigeria, Production, Processing
and Utilization, NRCRI Umudike. Pp94 – 100.
Onyenweaku, C. E.; B.C. Okoye; G.N. Asumugha; C.A. Okezie and L. Tanko (2008). “Economic
Assessment of the Trend in Cocoyam production in Nigeria” 1960/61 – 2006. Medwell
Agricultural Journal 3(2):99 – 101.
Onyenweaku, C.E. and D.O. Ohajianya (2005) “Technical efficiency of swamp and unpland rice
farms in south eastern Nigeria” Journal of Sustainable Tropical Agricultural Research 14:
64 – 70.
Onyenweaku, C.E. and E.O. Effiong (2005). “Technical Efficiency in Pig Production” in Akwa
Ibom State, Nigeria. Journal of Sustainable Tropical Agricultural Research. 6: 51 – 57.
Onyenweaku, C.E. and J. C. Nwaru (2005). “Application of Stochastic Frontier Production
Function to the Measurement of Technical Efficiency in Food Production” in Imo State,
Nigeria. Nigeria Agricultural Journal. . 36: 1 – 12.
Onyenweaku, C.E. K.C. Igwe and J.A. Mbanasor (2005). “Application for a Stochastic Frontier
Production Function to the Measurement of Technical Efficiency in Yam Production” in
Nasarawa State Nigeria, Journal of Sustainable Tropical Agriculture Research 13: 20 –
25.
Osagie, P.I. (1998). Transfer of Root Crop Technology for Alleviation of Poverty; the
contribution of shell, Nigeria. In Akoroda, M.O. and Ekanayake, I.J. (ed.) proceedings of
the 6th
Triennial Symposium of the International Society for Tropical Crops. 38-41.
Savanne, M. A. (1986). “The Effects of Social and Economic Changes on the Role and Status of
Women in sub-Saharan Africa”, In Moock, J.L. (ed). Understanding Africans Rural
Households and Farming Systems London: Westview Press.
Serem, A. K., V. Palapala, H. Talwana, J.M. Nandi, B. Ndabikunze and M.K. Koriri. (2008).
Socio-economic constraints to sustainable cocoyam production in the lake Victoria
crescent. African Journal of Environmental Science and Technology, Vol. 2(10): 305-308.
Thiam, A. B. E. Bravo – Ureta and T. Rivas (2001). Technical Efficiency in Developing Country
Agriculture: a meta-analysis. Agricultural Economics. 25: 235-243.
Ugboaja, M.O. (2007). “Gender Analysis of Rural Farmers Savings and Consumption Behaviour”
in Anambra State. An Unpublished Ph.D. Thesis, Department of Agriculture Economics.
University of Nigeria, Nsukka.
Uguru, M. I. (1996). Crop production, Tools, Techniques and Practices. Fulladu Publishing
Company. Enugu Nigeria.
Ugwu, S.I. (2007) “Resource Use Efficiency in the Production of Nsukka Yellow Pepper among
Rural Farmers in Nsukka Area”. An Unpublished M.Sc. Thesis, Department of Agriculture
Economics University of Nigeria, Nsukka.
Umoh, S. G. (2006): Resource use Efficiency in Urban Farming: An application of Stochastic
Frontier Production Accessed from Internal Journal of Agriculture and Biology 1560 –
8530/ 2006/ 08 – 1 – 38 – 44 from http://www.f.soybkusqers.org.
Upton, M. (1996). The Economics of Tropical Farming Systems, London: Cambridge University
Press pp. 3 – 7, 34-35, 293-294.
Uzokwe, U. N. (2009). “Gender Roles in Agricultural Production in the Seychelles Nigerian
Agricultural Journal 1: 37 – 43.
Verma, O.S. (2001). Gender Sensitization: Women in Agricultural Development. Journal of
Extension Systems 17(2): 83 – 93.
Wieczorek-Zeul, H. (2007). Without Women no Sustainable Development in Dembowski, H.ed.
Development and Cooperation International Journal. Pp 188 – 190.
World Bank (2005) Gender and Development, University Press, Baltimore.
World Bank (2006b). Policies for Pro-Poor Agricultural Growth, Africa Region, World Bank
Washington D.C. Mimeographed.
Yotopoulous, P.A. and Lau, L.J. (1973). Test of relative economic Efficiency; some further
results American Journal of Economics Review 63(1): 214 – 225.
APPENDIX 1
Table 1.1: Estimated Outputs of Major Agric Commodities (000 tonnes)
Item 2004 2003 2002 2001 2000
________________________________________________________________________
Cocoyam 3,500 3,500 3,929 3,886 3,385
Yam 27,000 27,000 26,849 26,201 25,873
Cassava 33,379 33,379 34,479 32,010 32,010
Potatoes 2,150 2,150 2,503 2,468 2,473
________________________________________________________________________
Source: FAO Statistics, 2005